A proteome-scale map of the human interactome network.

Just as reference genome sequences revolutionized human genetics, reference maps of interactome networks will be critical to fully understand genotype-phenotype relationships. Here, we describe a systematic map of ?14,000 high-quality human binary protein-protein interactions. At equal quality, this map is ?30% larger than what is available from small-scale studies published in the literature in the last few decades. While currently available information is highly biased and only covers a relatively small portion of the proteome, our systematic map appears strikingly more homogeneous, revealing a "broader" human interactome network than currently appreciated. The map also uncovers significant interconnectivity between known and candidate cancer gene products, providing unbiased evidence for an expanded functional cancer landscape, while demonstrating how high-quality interactome models will help "connect the dots" of the genomic revolution.

Safety and efficacy of flecainide associated with beta-blockers in arrhythmogenic right ventricular cardiomyopathy.

AIMS: Arrhythmogenic right ventricular cardiomyopathy (ARVC) is an inherited cardiomyopathy associated with a high risk of ventricular arrhythmia (VA). Current guidelines recommend beta-blockers as first-line medical therapy and if ineffective, sotalol or amiodarone. We describe our experience, as a tertiary centre for ARVC, with the effectiveness and tolerance of flecainide in addition to beta-blockers to prevent VA in ARVC. METHODS AND RESULTS: We retrospectively included 100 consecutive ARVC patients who received flecainide with beta-blockers between May 1999 and November 2017. Treatment persistence and related side effects were assessed, as was VA-free survival on treatment, 24-h Holter monitoring and programmed ventricular stimulation (PVS) off- and on-treatment. Tolerance was good, with 10% flecainide discontinuations (lack of efficacy in six, atrial fibrillation in one, and side effects in three). No Brugada-induced electrocardiography pattern on flecainide or haemodynamic impairment was reported. Premature ventricular contraction burden at 24-h Holter monitoring was significantly decreased under treatment [median 415 (interquartile range, IQR 97-730) vs. 2370 (1572-3400) at baseline, P < 0.0001, n = 46]. Among the 33 patients with PVS under treatment, PVS was positive in 40% on-treatment vs. 94% off-treatment (P < 0.001). During a median follow-up of 47 months (IQR 23-73), 22 patients presented sustained VA on treatment, corresponding to an event rate of 5% [95% confidence interval (CI) (0.6-9)] at 1 year and 25% [95% CI (14-35)] at 5 years under treatment. No patient died. CONCLUSION: This study suggests that flecainide and beta-blockers association is complementary to implantable cardioverter-defibrillator and catheter ablation and is safe for treating persistent symptomatic VA in patients with ARVC.

Operative list of genes associated with autism and neurodevelopmental disorders based on database review.

The genetics of neurodevelopmental disorders (NDD) has made tremendous progress during the last few decades with the identification of more than 1,500 genes associated with conditions such as intellectual disability and autism. The functional roles of these genes are currently studied to uncover the biological mechanisms influencing the clinical outcome of the mutation carriers. To integrate the data, several databases and curated gene lists have been generated. Here, we provide an overview of the main databases focusing on the genetics of NDD, that are widely used by the medical and scientific communities, and extract a list of high confidence NDD genes (HC-NDD). This gene set can be used as a first filter for interpreting large scale omics dataset or for diagnostic purposes. Overall HC-NDD genes (N = 1,586) are expressed at very early stages of fetal brain development and enriched in several biological pathways such as chromosome organization, cell cycle, metabolism and synaptic function. Among those HC-NDD genes, 204 (12,9%) are listed in the synaptic gene ontology SynGO and are enriched in genes expressed after birth in the cerebellum and the cortex of the human brain. Finally, we point at several limitations regarding the relatively poor standardized information available, especially on the carriers of the mutations. Progress on the phenotypic characterization and genetic profiling of the carriers will be crucial to improve our knowledge on the biological mechanisms and on risk and protective factors for NDD.

Systematic screening reveals a role for BRCA1 in the response to transcription-associated DNA damage.

BRCA1 is a breast and ovarian tumor suppressor. Given its numerous incompletely understood functions and the possibility that more exist, we performed complementary systematic screens in search of new BRCA1 protein-interacting partners. New BRCA1 functions and/or a better understanding of existing ones were sought. Among the new interacting proteins identified, genetic interactions were detected between BRCA1 and four of the interactors: TONSL, SETX, TCEANC, and TCEA2. Genetic interactions were also detected between BRCA1 and certain interactors of TONSL, including both members of the FACT complex. From these results, a new BRCA1 function in the response to transcription-associated DNA damage was detected. Specifically, new roles for BRCA1 in the restart of transcription after UV damage and in preventing or repairing damage caused by stabilized R loops were identified. These roles are likely carried out together with some of the newly identified interactors. This new function may be important in BRCA1 tumor suppression, since the expression of several interactors, including some of the above-noted transcription proteins, is repeatedly aberrant in both breast and ovarian cancers.

Proto-genes and de novo gene birth.

Novel protein-coding genes can arise either through re-organization of pre-existing genes or de novo. Processes involving re-organization of pre-existing genes, notably after gene duplication, have been extensively described. In contrast, de novo gene birth remains poorly understood, mainly because translation of sequences devoid of genes, or 'non-genic' sequences, is expected to produce insignificant polypeptides rather than proteins with specific biological functions. Here we formalize an evolutionary model according to which functional genes evolve de novo through transitory proto-genes generated by widespread translational activity in non-genic sequences. Testing this model at the genome scale in Saccharomyces cerevisiae, we detect translation of hundreds of short species-specific open reading frames (ORFs) located in non-genic sequences. These translation events seem to provide adaptive potential, as suggested by their differential regulation upon stress and by signatures of retention by natural selection. In line with our model, we establish that S. cerevisiae ORFs can be placed within an evolutionary continuum ranging from non-genic sequences to genes. We identify ~1,900 candidate proto-genes among S. cerevisiae ORFs and find that de novo gene birth from such a reservoir may be more prevalent than sporadic gene duplication. Our work illustrates that evolution exploits seemingly dispensable sequences to generate adaptive functional innovation.

Interpreting cancer genomes using systematic host network perturbations by tumour virus proteins.

Genotypic differences greatly influence susceptibility and resistance to disease. Understanding genotype-phenotype relationships requires that phenotypes be viewed as manifestations of network properties, rather than simply as the result of individual genomic variations. Genome sequencing efforts have identified numerous germline mutations, and large numbers of somatic genomic alterations, associated with a predisposition to cancer. However, it remains difficult to distinguish background, or 'passenger', cancer mutations from causal, or 'driver', mutations in these data sets. Human viruses intrinsically depend on their host cell during the course of infection and can elicit pathological phenotypes similar to those arising from mutations. Here we test the hypothesis that genomic variations and tumour viruses may cause cancer through related mechanisms, by systematically examining host interactome and transcriptome network perturbations caused by DNA tumour virus proteins. The resulting integrated viral perturbation data reflects rewiring of the host cell networks, and highlights pathways, such as Notch signalling and apoptosis, that go awry in cancer. We show that systematic analyses of host targets of viral proteins can identify cancer genes with a success rate on a par with their identification through functional genomics and large-scale cataloguing of tumour mutations. Together, these complementary approaches increase the specificity of cancer gene identification. Combining systems-level studies of pathogen-encoded gene products with genomic approaches will facilitate the prioritization of cancer-causing driver genes to advance the understanding of the genetic basis of human cancer.

An inter-species protein-protein interaction network across vast evolutionary distance.

In cellular systems, biophysical interactions between macromolecules underlie a complex web of functional interactions. How biophysical and functional networks are coordinated, whether all biophysical interactions correspond to functional interactions, and how such biophysical-versus-functional network coordination is shaped by evolutionary forces are all largely unanswered questions. Here, we investigate these questions using an "inter-interactome" approach. We systematically probed the yeast and human proteomes for interactions between proteins from these two species and functionally characterized the resulting inter-interactome network. After a billion years of evolutionary divergence, the yeast and human proteomes are still capable of forming a biophysical network with properties that resemble those of intra-species networks. Although substantially reduced relative to intra-species networks, the levels of functional overlap in the yeast-human inter-interactome network uncover significant remnants of co-functionality widely preserved in the two proteomes beyond human-yeast homologs. Our data support evolutionary selection against biophysical interactions between proteins with little or no co-functionality. Such non-functional interactions, however, represent a reservoir from which nascent functional interactions may arise.

Protein domain-level landscape of cancer-type-specific somatic mutations.

Identifying driver mutations and their functional consequences is critical to our understanding of cancer. Towards this goal, and because domains are the functional units of a protein, we explored the protein domain-level landscape of cancer-type-specific somatic mutations. Specifically, we systematically examined tumor genomes from 21 cancer types to identify domains with high mutational density in specific tissues, the positions of mutational hotspots within these domains, and the functional and structural context where possible. While hotspots corresponding to specific gain-of-function mutations are expected for oncoproteins, we found that tumor suppressor proteins also exhibit strong biases toward being mutated in particular domains. Within domains, however, we observed the expected patterns of mutation, with recurrently mutated positions for oncogenes and evenly distributed mutations for tumor suppressors. For example, we identified both known and new endometrial cancer hotspots in the tyrosine kinase domain of the FGFR2 protein, one of which is also a hotspot in breast cancer, and found new two hotspots in the Immunoglobulin I-set domain in colon cancer. Thus, to prioritize cancer mutations for further functional studies aimed at more precise cancer treatments, we have systematically correlated mutations and cancer types at the protein domain level.

Genome-wide replication landscape of Candida glabrata.

BACKGROUND: The opportunistic pathogen Candida glabrata is a member of the Saccharomycetaceae yeasts. Like its close relative Saccharomyces cerevisiae, it underwent a whole-genome duplication followed by an extensive loss of genes. Its genome contains a large number of very long tandem repeats, called megasatellites. In order to determine the whole replication program of the C. glabrata genome and its general chromosomal organization, we used deep-sequencing and chromosome conformation capture experiments. RESULTS: We identified 253 replication fork origins, genome wide. Centromeres, HML and HMR loci, and most histone genes are replicated early, whereas natural chromosomal breakpoints are located in late-replicating regions. In addition, 275 autonomously replicating sequences (ARS) were identified during ARS-capture experiments, and their relative fitness was determined during growth competition. Analysis of ARSs allowed us to identify a 17-bp consensus, similar to the S. cerevisiae ARS consensus sequence but slightly more constrained. Megasatellites are not in close proximity to replication origins or termini. Using chromosome conformation capture, we also show that early origins tend to cluster whereas non-subtelomeric megasatellites do not cluster in the yeast nucleus. CONCLUSIONS: Despite a shorter cell cycle, the C. glabrata replication program shares unexpected striking similarities to S. cerevisiae, in spite of their large evolutionary distance and the presence of highly repetitive large tandem repeats in C. glabrata. No correlation could be found between the replication program and megasatellites, suggesting that their formation and propagation might not be directly caused by replication fork initiation or termination.

Exploration of binary virus-host interactions using an infectious protein complementation assay.

A precise mapping of pathogen-host interactions is essential for comprehensive understanding of the processes of infection and pathogenesis. The most frequently used techniques for interactomics are the yeast two-hybrid binary methodologies, which do not recapitulate the pathogen life cycle, and the tandem affinity purification mass spectrometry co-complex methodologies, which cannot distinguish direct from indirect interactions. New technologies are thus needed to improve the mapping of pathogen-host interactions. In the current study, we detected binary interactions between influenza A virus polymerase and host proteins during the course of an actual viral infection, using a new strategy based on trans-complementation of the Gluc1 and Gluc2 fragments of Gaussia princeps luciferase. Infectious recombinant influenza viruses that encode a Gluc1-tagged polymerase subunit were engineered to infect cultured cells transiently expressing a selected set of Gluc2-tagged cellular proteins involved in nucleocytoplasmic trafficking pathways. A random set and a literature-curated set of Gluc2-tagged cellular proteins were tested in parallel. Our assay allowed the sensitive and accurate recovery of previously described interactions, and it revealed 30% of positive, novel viral-host protein-protein interactions within the exploratory set. In addition to cellular proteins involved in the nuclear import pathway, components of the nuclear pore complex such as NUP62 and mRNA export factors such as NXF1, RMB15B, and DDX19B were identified for the first time as interactors of the viral polymerase. Gene silencing experiments further showed that NUP62 is required for efficient viral replication. Our findings give new insights regarding the subversion of host nucleocytoplasmic trafficking pathways by influenza A viruses. They also demonstrate the potential of our infectious protein complementation assay for high-throughput exploration of influenza virus interactomics in infected cells. With more infectious reverse genetics systems becoming available, this strategy should be widely applicable to numerous pathogens.

A foundational atlas of autism protein interactions reveals molecular convergence.

Translating high-confidence (hc) autism spectrum disorder (ASD) genes into viable treatment targets remains elusive. We constructed a foundational protein-protein interaction (PPI) network in HEK293T cells involving 100 hcASD risk genes, revealing over 1,800 PPIs (87% novel). Interactors, expressed in the human brain and enriched for ASD but not schizophrenia genetic risk, converged on protein complexes involved in neurogenesis, tubulin biology, transcriptional regulation, and chromatin modification. A PPI map of 54 patient-derived missense variants identified differential physical interactions, and we leveraged AlphaFold-Multimer predictions to prioritize direct PPIs and specific variants for interrogation in Xenopus tropicalis and human forebrain organoids. A mutation in the transcription factor FOXP1 led to reconfiguration of DNA binding sites and altered development of deep cortical layer neurons in forebrain organoids. This work offers new insights into molecular mechanisms underlying ASD and describes a powerful platform to develop and test therapeutic strategies for many genetically-defined conditions.

Dissecting the 22q13 region to explore the genetic and phenotypic diversity of patients with Phelan-McDermid syndrome.

SHANK3-related Phelan-McDermid syndrome (PMS) is caused by a loss of the distal part of chromosome 22, including SHANK3, or by a pathological SHANK3 variant. There is an important genetic and phenotypic diversity among patients who can present with developmental delay, language impairments, autism, epilepsy, and other symptoms. SHANK3, encoding a synaptic scaffolding protein, is deleted in the majority of patients with PMS and is considered a major gene involved in the neurological impairments of the patients. However, differences in deletion size can influence clinical features, and in some rare cases, deletions at the 22q13 locus in individuals with SHANK3-unrelated PMS do not encompass SHANK3. These individuals with SHANK3-unrelated PMS still display a PMS-like phenotype. This suggests the participation of other 22q13 genes in the pathogenesis of PMS. Here, we review the biological function and potential implication in PMS symptoms of 110 genes located in the 22q13 region, focusing on 35 genes with evidence for association with neurodevelopmental disorders, including 13 genes for epilepsy and 11 genes for microcephaly and/or macrocephaly. Our review is restricted to the 22q13 region, but future large-scale studies using whole genome sequencing and deep-phenotyping are warranted to develop predictive models of clinical trajectories and to target specific medical and educational care for each individual with PMS.

Phenotypic effects of genetic variants associated with autism.

While over 100 genes have been associated with autism, little is known about the prevalence of variants affecting them in individuals without a diagnosis of autism. Nor do we fully appreciate the phenotypic diversity beyond the formal autism diagnosis. Based on data from more than 13,000 individuals with autism and 210,000 undiagnosed individuals, we estimated the odds ratios for autism associated to rare loss-of-function (LoF) variants in 185 genes associated with autism, alongside 2,492 genes displaying intolerance to LoF variants. In contrast to autism-centric approaches, we investigated the correlates of these variants in individuals without a diagnosis of autism. We show that these variants are associated with a small but significant decrease in fluid intelligence, qualification level and income and an increase in metrics related to material deprivation. These effects were larger for autism-associated genes than in other LoF-intolerant genes. Using brain imaging data from 21,040 individuals from the UK Biobank, we could not detect significant differences in the overall brain anatomy between LoF carriers and non-carriers. Our results highlight the importance of studying the effect of the genetic variants beyond categorical diagnosis and the need for more research to understand the association between these variants and sociodemographic factors, to best support individuals carrying these variants.

Genetic Heterogeneity Shapes Brain Connectivity in Psychiatry.

BACKGROUND: Polygenicity and genetic heterogeneity pose great challenges for studying psychiatric conditions. Genetically informed approaches have been implemented in neuroimaging studies to address this issue. However, the effects on functional connectivity of rare and common genetic risks for psychiatric disorders are largely unknown. Our objectives were to estimate and compare the effect sizes on brain connectivity of psychiatric genomic risk factors with various levels of complexity: oligogenic copy number variants (CNVs), multigenic CNVs, and polygenic risk scores (PRSs) as well as idiopathic psychiatric conditions and traits. METHODS: Resting-state functional magnetic resonance imaging data were processed using the same pipeline across 9 datasets. Twenty-nine connectome-wide association studies were performed to characterize the effects of 15 CNVs (1003 carriers), 7 PRSs, 4 idiopathic psychiatric conditions (1022 individuals with autism, schizophrenia, bipolar conditions, or attention-deficit/hyperactivity disorder), and 2 traits (31,424 unaffected control subjects). RESULTS: Effect sizes on connectivity were largest for psychiatric CNVs (estimates: 0.2-0.65 z score), followed by psychiatric conditions (0.15-0.42), neuroticism and fluid intelligence (0.02-0.03), and PRSs (0.01-0.02). Effect sizes of CNVs on connectivity were correlated to their effects on cognition and risk for disease (r = 0.9, p = 5.93 × 10-6). However, effect sizes of CNVs adjusted for the number of genes significantly decreased from small oligogenic to large multigenic CNVs (r = -0.88, p = 8.78 × 10-6). PRSs had disproportionately low effect sizes on connectivity compared with CNVs conferring similar risk for disease. CONCLUSIONS: Heterogeneity and polygenicity affect our ability to detect brain connectivity alterations underlying psychiatric manifestations.

Comparative genomics of protoploid Saccharomycetaceae.

Our knowledge of yeast genomes remains largely dominated by the extensive studies on Saccharomyces cerevisiae and the consequences of its ancestral duplication, leaving the evolution of the entire class of hemiascomycetes only partly explored. We concentrate here on five species of Saccharomycetaceae, a large subdivision of hemiascomycetes, that we call "protoploid" because they diverged from the S. cerevisiae lineage prior to its genome duplication. We determined the complete genome sequences of three of these species: Kluyveromyces (Lachancea) thermotolerans and Saccharomyces (Lachancea) kluyveri (two members of the newly described Lachancea clade), and Zygosaccharomyces rouxii. We included in our comparisons the previously available sequences of Kluyveromyces lactis and Ashbya (Eremothecium) gossypii. Despite their broad evolutionary range and significant individual variations in each lineage, the five protoploid Saccharomycetaceae share a core repertoire of approximately 3300 protein families and a high degree of conserved synteny. Synteny blocks were used to define gene orthology and to infer ancestors. Far from representing minimal genomes without redundancy, the five protoploid yeasts contain numerous copies of paralogous genes, either dispersed or in tandem arrays, that, altogether, constitute a third of each genome. Ancient, conserved paralogs as well as novel, lineage-specific paralogs were identified.

Dynamic evolution of megasatellites in yeasts.

Megasatellites are a new family of long tandem repeats, recently discovered in the yeast Candida glabrata. Compared to shorter tandem repeats, such as minisatellites, megasatellite motifs range in size from 135 to more than 300 bp, and allow calculation of evolutionary distances between individual motifs. Using divergence based on nucleotide substitutions among similar motifs, we determined the smallest distance between two motifs, allowing their subsequent clustering. Motifs belonging to the same cluster are recurrently found in different megasatellites located on different chromosomes, showing transfer of genetic information between megasatellites. In comparison, evolution of the few similar tandem repeats in Saccharomyces cerevisiae FLO genes mainly involves subtelomeric homologous recombination. We estimated selective constraints acting on megasatellite motifs and their host genes, and found that motifs are under strong purifying selection. Surprisingly, motifs inserted within pseudogenes are also under purifying selection, whereas the pseudogenes themselves evolve neutrally. We propose that megasatellite motifs propagate by a combination of three different molecular mechanisms: (i) gene duplication, (ii) ectopic homologous recombination and (iii) transfer of motifs from one megasatellite to another one. These mechanisms actively cooperate to create new megasatellites, that may play an important role in the adaptation of Candida glabrata to its human host.

Genetic correlates of phenotypic heterogeneity in autism.

The substantial phenotypic heterogeneity in autism limits our understanding of its genetic etiology. To address this gap, here we investigated genetic differences between autistic individuals (nmax = 12,893) based on core and associated features of autism, co-occurring developmental disabilities and sex. We conducted a comprehensive factor analysis of core autism features in autistic individuals and identified six factors. Common genetic variants were associated with the core factors, but de novo variants were not. We found that higher autism polygenic scores (PGS) were associated with lower likelihood of co-occurring developmental disabilities in autistic individuals. Furthermore, in autistic individuals without co-occurring intellectual disability (ID), autism PGS are overinherited by autistic females compared to males. Finally, we observed higher SNP heritability for autistic males and for autistic individuals without ID. Deeper phenotypic characterization will be critical in determining how the complex underlying genetics shape cognition, behavior and co-occurring conditions in autism.

Color Tuning by Oxide Addition in PEDOT:PSS-Based Electrochromic Devices.

Poly(3,4-ethylenedi-oxythiophene) (PEDOT) derivatives conducting polymers are known for their great electrochromic (EC) properties offering a reversible blue switch under an applied voltage. Characterizations of symmetrical EC devices, built on combinations of PEDOT thin films, deposited with a bar coater from commercial inks, and separated by a lithium-based ionic membrane, show highest performance for 800 nm thickness. Tuning of the color is further achieved by mixing the PEDOT film with oxides. Taking, in particular, the example of optically inactive iron oxide Fe2O3, a dark blue to reddish switch, of which intensity depends on the oxide content, is reported. Careful evaluation of the chromaticity parameters L*, a*, and b*, with oxidizing/reducing potentials, evidences a possible monitoring of the bluish tint.

Erratum: Author Correction: A framework to identify contributing genes in patients with Phelan-McDermid syndrome.

[This corrects the article DOI: 10.1038/s41525-017-0035-2.].

Heritability of the melatonin synthesis variability in autism spectrum disorders.

Autism Spectrum Disorders (ASD) are heterogeneous neurodevelopmental disorders with a complex genetic architecture. They are characterized by impaired social communication, stereotyped behaviors and restricted interests and are frequently associated with comorbidities such as intellectual disability, epilepsy and severe sleep disorders. Hyperserotonemia and low melatonin levels are among the most replicated endophenotypes reported in ASD, but their genetic causes remain largely unknown. Based on the biochemical profile of 717 individuals including 213 children with ASD, 128 unaffected siblings and 376 parents and other relatives, we estimated the heritability of whole-blood serotonin, platelet N-acetylserotonin (NAS) and plasma melatonin levels, as well as the two enzymes arylalkylamine N-acetyltransferase (AANAT) and acetylserotonin O-methyltransferase (ASMT) activities measured in platelets. Overall, heritability was higher for NAS (0.72 ± 0.091) and ASMT (0.59 ± 0.097) compared with serotonin (0.31 ± 0.078), AANAT (0.34 ± 0.077) and melatonin (0.22 ± 0.071). Bivariate analyses showed high phenotypic and genetic correlations between traits of the second step of the metabolic pathway (NAS, ASMT and melatonin) indicating the contribution of shared genetic factors. A better knowledge of the heritability of the melatonin synthesis variability constitutes an important step to identify the factors that perturb this pathway in individuals with ASD.