Nadia Chuzhanova

We propose a computational framework for selecting biologically plausible genes identified by clustering of multi-omics data that reveal patients’ similarity, thus giving researchers a more comprehensive view on any given disease. We employ spectral clustering of a similarity network created by fusion of three similarity networks, based on mRNA expression of immune genes, miRNA expression and DNA methylation data, using SNF_v2.1 software. For each cluster, we rank multi-omics features, ensuring the best separation between clusters, and select the top-ranked features that preserve clustering. To find genes targeted by DNA methylation and miRNAs found in the top-ranked features, we use chromosome-conformation capture data and miRNet2.0 software, respectively. To identify informative genes, these combined sets of target genes are analyzed in terms of their enrichment in somatic/germline mutations, GO biological processes/pathways terms and known sets of genes considered to be important in relation to a given disease, as recorded in the Molecular Signature Database from GSEA. The protein–protein interaction (PPI) networks were analyzed to identify genes that are hubs of PPI networks. We used data recorded in The Cancer Genome Atlas for patients with acute myeloid leukemia to demonstrate our approach, and discuss our findings in the context of results in the literature.

Understanding structure--function relationships in the brain remains an important challenge in neuroscience. However, whilst structural brain networks are intrinsically directed, due to the prevalence of chemical synapses in the cortex, most studies in network neuroscience represent the brain as an undirected network. Here, we explore the role that directionality plays in shaping transition dynamics of functional brain states. Using a system of Hopfield neural elements with heterogeneous structural connectivity given by different species and parcellations (cat, Caenorhabditis elegans and two macaque networks), we investigate the effect of removing directionality of connections on brain capacity, which we quantify via its ability to store attractor states. In addition to determining large numbers of fixed-point attractor sets, we deploy the recently developed basin stability technique in order to assess the global stability of such brain states, which can be considered a proxy for network state robustness. Our study indicates that not only can directed network topology have a significant effect on the information capacity of connectome-based networks, but it can also impact significantly the domains of attraction of the aforementioned brain states. In particular, we find network modularity to be a key mechanism underlying the formation of neural activity patterns, and moreover, our results suggest that neglecting network directionality has the scope to eliminate states that correlate highly with the directed modular structure of the brain. A numerical analysis of the distribution of attractor states identified a small set of prototypical direction-dependent activity patterns that potentially constitute a `skeleton' of the non-stationary dynamics typically observed in the brain. This study thereby emphasizes the substantial role network directionality can have in shaping the brain's ability to both store and process information.

Despite a growing number of studies on longevity in Drosophila, genetic factors influencing lifespan are still poorly understood. In this paper we propose a conceptually new approach for the identification of novel longevity-associated genes and potential target genes for SNPs in non-coding regions by utilizing the knowledge of co-location of various loci, governed by the three-dimensional architecture of the Drosophila genome. Firstly, we created networks between genes/genomic regions harboring SNPs deemed to be significant in two longevity GWAS summary statistics datasets using intra- and inter-chromosomal interaction frequencies (Hi-C data) as a measure of co-location. These networks were further extended to include regions strongly interacting with previously selected regions. Using various network measures, literature search and additional bioinformatics resources, we investigated the plausibility of genes found to have genuine association with longevity. Several of the newly identified genes were common between the two GWAS datasets and these possessed human orthologs. We also found that the proportion of non-coding SNPs in borders between topologically associated domains is significantly higher than expected by chance. Assuming co-location, we investigated potential target genes for non-coding SNPs. This approach therefore offers a stepping stone to identification of novel genes and SNP targets linked to human longevity.

Genome-wide association studies identified numerous loci harbouring single nucleotide polymorphisms (SNPs) associated with various human diseases, although the causal role of many of them remains unknown. In this paper, we postulate that co-location and shared biological function of novel genes with genes known to associate with a specific phenotype make them potential candidates linked to the same phenotype (“guilt-by-proxy”). We propose a novel network-based approach for predicting candidate genes/genomic regions utilising the knowledge of the 3D architecture of the human genome and GWAS data. As a case study we used a well-studied polygenic disorder ‒ schizophrenia ‒ for which we compiled a comprehensive dataset of SNPs. Our approach revealed 634 novel regions covering ~398 Mb of the human genome and harbouring ~9000 genes. Using various network measures and enrichment analysis, we identified subsets of genes and investigated the plausibility of these genes/regions having an association with schizophrenia using literature search and bioinformatics resources. We identified several genes/regions with previously reported associations with schizophrenia, thus providing proof-of-concept, as well as novel candidates with no prior known associations. This approach has the potential to identify novel genes/genomic regions linked to other polygenic disorders and provide means of aggregating genes/SNPs for further investigation.

Missense/nonsense mutations and microdeletions/microinsertions (<21 bp) represent ∼76% of all mutations causing human inherited disease, and their occurrence has been associated with sequence motifs (direct, inverted, and mirror repeats; G‐quartets) capable of adopting non‐B DNA structures. We found that a significant proportion (∼21%) of both microdeletions and microinsertions occur within direct repeats, and are explicable by slipped misalignment. A novel mutational mechanism, DNA triplex formation followed by DNA repair, may explain ∼5% of microdeletions and microinsertions at mirror repeats. Further, G‐quartets, direct, and inverted repeats also appear to play a prominent role in mediating missense mutations, whereas only direct and inverted repeats mediate nonsense mutations. We suggest a mutational mechanism involving slipped strand mispairing, slipped structure formation, and DNA repair, to explain ∼15% of missense and ∼12% of nonsense mutations yielding perfect direct repeats from imperfect repeats, or the extension of existing direct repeats. Similar proportions of missense and nonsense mutations were explicable by hairpin/loop formation and DNA repair, yielding perfect inverted repeats from imperfect repeats. We also propose a model for single base‐pair substitution based on one‐electron oxidation reactions at G‐quadruplex DNA. Overall, the proposed mechanisms provide support for a role for non‐B DNA structures in human gene mutagenesis.

Facioscapulohumeral dystrophy (FSHD) is commonly associated with contraction of the D4Z4 macro-satellite repeat on chromosome 4q35 (FSHD1) or mutations in the SMCHD1 gene (FSHD2). Recent studies have shown that the clinical manifestation of FSHD1 can be modified by mutations in the SMCHD1 gene within a given family. The absence of either D4Z4 contraction or SMCHD1 mutations in a small cohort of patients suggests that the disease could also be due to disruption of gene regulation. In this study, we postulated that mutations responsible for exerting a modifier effect on FSHD might reside within remotely acting regulatory elements that have the potential to interact at a distance with their cognate gene promoter via chromatin looping. To explore this postulate, genome-wide Hi-C data were used to identify genomic fragments displaying the strongest interaction with the SMCHD1 gene. These fragments were then narrowed down to shorter regions using ENCODE and FANTOM data on transcription factor binding sites and epigenetic marks characteristic of promoters, enhancers and silencers. We identified two regions, located respectively ~14 and ~85 kb upstream of the SMCHD1 gene, which were then sequenced in 229 FSHD/FSHD-like patients (200 with D4Z4 repeat units SMCHD1 gene. One of these variants was found to be of potential functional significance based on DNA methylation analysis. Further functional ascertainment will be required in order to establish the clinical/functional significance of the variants found. In this study, we propose an improved approach to predict the possible locations of remotely acting regulatory elements that might influence the transcriptional regulation of their associated gene(s). It represents a new way to screen for disease-relevant mutations beyond the immediate vicinity of the specific disease gene. It promises to be useful for investigating disorders in which mutations could occur in remotely acting regulatory elements.

Neurofibromatosis type 1 (NF1), a neuroectodermal disorder, is caused by germline mutations in the NF1 gene. NF1 affects approximately 1/3,000 individuals worldwide, with about 50% of cases representing de novo mutations. Although the NF1 gene was identified in 1990, the underlying gene mutations still remain undetected in a small but obdurate minority of NF1 patients. We postulated that in these patients, hitherto undetected pathogenic mutations might occur in regulatory elements far upstream of the NF1 gene. In an attempt to identify such remotely acting regulatory elements, we reasoned that some of them might reside within DNA sequences that (1) have the potential to interact at distance with the NF1 gene and (2) lie within a histone H3K27ac-enriched region, a characteristic of active enhancers. Combining Hi-C data, obtained by means of the chromosome conformation capture technique, with data on the location and level of histone H3K27ac enrichment upstream of the NF1 gene, we predicted in silico the presence of two remotely acting regulatory regions, located, respectively, approximately 600 kb and approximately 42 kb upstream of the NF1 gene. These regions were then sequenced in 47 NF1 patients in whom no mutations had been found in either the NF1 or SPRED1 gene regions. Five patients were found to harbour DNA sequence variants in the distal H3K27ac-enriched region. Although these variants are of uncertain pathological significance and still remain to be functionally characterized, this approach promises to be of general utility for the detection of mutations underlying other inherited disorders that may be caused by mutations in remotely acting regulatory elements.

Ornithine carbamoyltransferase deficiency is the most common inherited defect of the urea cycle. We examined 28 male and 9 female patients from 29 families and identified 25 distinct mutations in OTC, 14 of which were novel. Three novel missense mutations (p.Ala102Pro, p.Pro158Ser, p.Lys210Glu) and a novel deletion of the Leu43 are not directly involved either in the enzyme active site or in the intersubunit interactions; however, the mutations include conserved residues involved in intramolecular interaction network essential for the function of the enzyme. Three novel large deletions – a 444 kb deletion affecting RPGR, OTC and TSPAN7, a 10 kb‐deletion encompassing OTC exons 5 and 6 and a 24.5 kb‐deletion encompassing OTC exons 9 and 10 – have probably been initiated by double strand breaks at recombination‐promoting motifs with subsequent non‐homologous end joining repair. Finally, we present a manifesting heterozygote carrying a hypomorphic mutation p.Arg129His in combination with unfavorably skewed X‐inactivation in three peripheral tissues.

Species of Cronobacter are widespread in the environment and are occasional food-borne pathogens associated with serious neonatal diseases, including bacteraemia, meningitis, and necrotising enterocolitis. The genus is composed of seven species: C. sakazakii, C. malonaticus, C. turicensis, C. dublinensis, C. muytjensii, C. universalis, and C. condimenti. Clinical cases are associated with three species, C. malonaticus, C. turicensis and, in particular, with C. sakazakii multilocus sequence type 4. Thus, it is plausible that virulence determinants have evolved in certain lineages. We generated high quality sequence drafts for eleven Cronobacter genomes representing the seven Cronobacter species, including an ST4 strain of C. sakazakii. Comparative analysis of these genomes together with the two publicly available genomes revealed Cronobacter has over 6,000 genes in one or more strains and over 2,000 genes shared by all Cronobacter. Considerable variation in the presence of traits such as type six secretion systems, metal resistance (tellurite, copper and silver), and adhesins were found. C. sakazakii is unique in the Cronobacter genus in encoding genes enabling the utilization of exogenous sialic acid which may have clinical significance. The C. sakazakii ST4 strain 701 contained additional genes as compared to other C. sakazakii but none of them were known specific virulence-related genes. Genome comparison revealed that pair-wise DNA sequence identity varies between 89 and 97% in the seven Cronobacter species, and also suggested various degrees of divergence. Sets of universal core genes and accessory genes unique to each strain were identified. These gene sequences can be used for designing genus/species specific detection assays. Genes encoding adhesins, T6SS, and metal resistance genes as well as prophages are found in only subsets of genomes and have contributed considerably to the variation of genomic content. Differences in gene content likely contribute to differences in the clinical and environmental distribution of species and sequence types.

Neurofibromatosis type 1 (NF1) is a complex neurocutaneous disorder with an increased susceptibility to develop both benign and malignant tumors but with a wide spectrum of inter and intrafamilial clinical variability. The establishment of genotype-phenotype associations in NF1 is potentially useful for targeted therapeutic intervention but has generally been unsuccessful, apart from small subsets of molecularly defined patients. The objective of this study was to evaluate the clinical phenotype associated with the specific types ofNF1mutation in a retrospectively recorded clinical dataset comprising 149NF1mutation-known individuals from unrelated families. Each patient was assessed for ten NF1-related clinical features, including the number of café-au-lait spots, cutaneous and subcutaneous neurofibromas and the presence/absence of intertriginous skin freckling, Lisch nodules, plexiform and spinal neurofibromas, optic gliomas, other neoplasms (in particular CNS gliomas, malignant peripheral nerve sheath tumors (MPNSTs), juvenile myelomonocytic leukemia, rhabdomyosarcoma, phaechromocytoma, gastrointestinal stromal tumors, juvenile xanthogranuloma, and lipoma) and evidence of learning difficulties. Gender and age at examination were also recorded. Patients were subcategorized according to their associatedNF1germ line mutations: frame shift deletions (52), splice-site mutations (23), nonsense mutations (36), missense mutations (32) and other types of mutation (6). A significant association was apparent between possession of a splice-site mutation and the presence of brain gliomas and MPNSTs (p = 0.006). If confirmed, these findings are likely to be clinically important since up to a third of NF1 patients harbor splice-site mutations. A significant influence of gender was also observed on the number of subcutaneous neurofibromas (females,p = 0.009) and preschool learning difficulties (females,p = 0.022).