Large regions of prokaryotic genomes are currently without any annotation, in part due to well-established limitations of annotation tools. For example, it is routine for genes using alternative start codons to be misreported or completely omitted. Therefore, we present StORF-Reporter, a tool that takes an annotated genome and returns regions that may contain missing CDS genes from unannotated regions. StORF-Reporter consists of two parts. The first begins with the extraction of unannotated regions from an annotated genome. Next, Stop-ORFs (StORFs) are identified in these unannotated regions. StORFs are open reading frames that are delimited by stop codons and thus can capture those genes most often missing in genome annotations. We show this methodology recovers genes missing from canonical genome annotations. We inspect the results of the genomes of model organisms, the pangenome of Escherichia coli, and a set of 5109 prokaryotic genomes of 247 genera from the Ensembl Bacteria database. StORF-Reporter extended the core, soft-core and accessory gene collections, identified novel gene families and extended families into additional genera. The high levels of sequence conservation observed between genera suggest that many of these StORFs are likely to be functional genes that should now be considered for inclusion in canonical annotations.

Several studies have compared various features of heritable disease genes with other so called non-disease genes, but they have yielded some conflicting results. A potential problem in those studies is that the non-disease genes contained a large number of essential genes--genes which are indispensable for humans to survive and reproduce. Since a functional disruption of an essential gene has fatal consequences, it's more reasonable to regard essential genes as extremely severe "disease" genes. Here we perform a comparative study on the features of human essential, disease, and other genes.

In order to describe a cell at molecular level, a notion of a "gene" is neither necessary nor helpful. It is sufficient to consider the molecules (i.e., chromosomes, transcripts, proteins) and their interactions to describe cellular processes. The downside of the resulting high resolution is that it becomes very tedious to address features on the organismal and phenotypic levels with a language based on molecular terms. Looking for the missing link between biological disciplines dealing with different levels of biological organization, we suggest to return to the original intent behind the term "gene". To this end, we propose to investigate whether a useful notion of "gene" can be constructed based on an underlying notion of function, and whether this can serve as the necessary link and embed the various distinct gene concepts of biological (sub)disciplines in a coherent theoretical framework. In reply to the Genon Theory recently put forward by Klaus Scherrer and Jürgen Jost in this journal, we shall discuss a general approach to assess a gene definition that should then be tested for its expressiveness and potential cross-disciplinary relevance.

Eukaryotes are typically depicted as descendants of archaea, but their genomes are evolutionary chimeras with genes stemming from archaea and bacteria. Which prokaryotic heritage predominates? Here, we have clustered 19,050,992 protein sequences from 5,443 bacteria and 212 archaea with 3,420,731 protein sequences from 150 eukaryotes spanning six eukaryotic supergroups. By downsampling, we obtain estimates for the bacterial and archaeal proportions. Eukaryotic genomes possess a bacterial majority of genes. On average, the majority of bacterial genes is 56% overall, 53% in eukaryotes that never possessed plastids, and 61% in photosynthetic eukaryotic lineages, where the cyanobacterial ancestor of plastids contributed additional genes to the eukaryotic lineage. Intracellular parasites, which undergo reductive evolution in adaptation to the nutrient rich environment of the cells that they infect, relinquish bacterial genes for metabolic processes. Such adaptive gene loss is most pronounced in the human parasite Encephalitozoon intestinalis with 86% archaeal and 14% bacterial derived genes. The most bacterial eukaryote genome sampled is rice, with 67% bacterial and 33% archaeal genes. The functional dichotomy, initially described for yeast, of archaeal genes being involved in genetic information processing and bacterial genes being involved in metabolic processes is conserved across all eukaryotic supergroups.

We have generated several hundred lines of zebrafish (Danio rerio), each heterozygous for a recessive embryonic lethal mutation. Since many tumor suppressor genes are recessive lethals, we screened our colony for lines that display early mortality and/or gross evidence of tumors. We identified 12 lines with elevated cancer incidence. Fish from these lines develop malignant peripheral nerve sheath tumors, and in some cases also other tumor types, with moderate to very high frequencies. Surprisingly, 11 of the 12 lines were each heterozygous for a mutation in a different ribosomal protein (RP) gene, while one line was heterozygous for a mutation in a zebrafish paralog of the human and mouse tumor suppressor gene, neurofibromatosis type 2. Our findings suggest that many RP genes may act as haploinsufficient tumor suppressors in fish. Many RP genes might also be cancer genes in humans, where their role in tumorigenesis could easily have escaped detection up to now.

Autophagy is a protective and life-sustaining process in which cytoplasmic components are packaged into double-membrane vesicles and targeted to lysosomes for degradation. Accumulating evidence supports that autophagy is associated with several pathological conditions. However, research on the functional cross-links between autophagy and disease genes remains in its early stages. In this study, we constructed a disease-autophagy network (DAN) by integrating known disease genes, known autophagy genes and protein-protein interactions (PPI). Dissecting the topological properties of the DAN suggested that nodes that both autophagy and disease genes (inter-genes), are topologically important in the DAN structure. Next, a core network from the DAN was extracted to analyze the functional links between disease and autophagy genes. The genes in the core network were significantly enriched in multiple disease-related pathways, suggesting that autophagy genes may function in various disease processes. Of 17 disease classes, 11 significantly overlapped with autophagy genes, including cancer diseases, metabolic diseases and hematological diseases, a finding that is supported by the literatures. We also found that autophagy genes have a bridging role in the connections between pairs of disease classes. Altogether, our study provides a better understanding of the molecular mechanisms underlying human diseases and the autophagy process.

The formation of new genes by combining parts of existing genes is an important evolutionary process. Remodelled genes, which we call composites, have been investigated in many species, however, their distribution across all of life is still unknown. We set out to examine the extent to which genomes from cells and mobile genetic elements contain composite genes. We identify composite genes as those that show partial homology to at least two unrelated component genes. In order to identify composite and component genes, we constructed sequence similarity networks (SSNs) of more than one million genes from all three domains of life, as well as viruses and plasmids. We identified non-transitive triplets of nodes in this network and explored the homology relationships in these triplets to see if the middle nodes were indeed composite genes. In total, we identified 221,043 (18.57%) composites genes, which were distributed across all genomic and functional categories. In particular, the presence of composite genes is statistically more likely in eukaryotes than prokaryotes.

One of the main issues of molecular evolution is to divulge the principles in dictating the evolutionary rate differences among various gene classes. Immunological genes have received considerable attention in evolutionary biology as candidates for local adaptation and for studying functionally important polymorphisms. The normal structure and function of immunological genes will be distorted when they experience mutations leading to immunological dysfunctions.

Worldwide, the incidence of obesity has increased dramatically over the past decades. More knowledge about the complex etiology of obesity is needed in order to find additional approaches for treatment and prevention. Investigating the exome sequencing data of 30 extremely obese subjects (BMI 45-65 kg/m(2)) shows that predicted damaging missense variants in olfactory receptor genes on chromosome 1q and rare predicted damaging variants in the protocadherin (PCDH) beta-cluster genes on chromosome 5q31, reported in our previous work, co-localize in subjects with extreme obesity. This implies a synergistic effect between genetic variation in these gene clusters in the predisposition to extreme obesity. Evidence for a general involvement of the olfactory transduction pathway on itself could not be found. Bioinformatic analysis indicates a specific involvement of the PCDH beta-cluster genes in controlling tissue development. Further mechanistic insight needs to await the identification of the ligands of the 1q olfactory receptors. Eventually, this may provide the possibility to manipulate food flavor in a way to reduce the risk of overeating and of extreme obesity in genetically predisposed subjects.

Well known for its gene density and the large number of mapped diseases, the human sub-chromosomal region Xq28 has long been a focus of genome research. Over 40 of approximately 300 X-linked diseases map to this region, and systematic mapping, transcript identification, and mutation analysis has led to the identification of causative genes for 26 of these diseases, leaving another 17 diseases mapped to Xq28, where the causative gene is still unknown. To expedite disease gene identification, we have initiated the functional characterisation of all known Xq28 genes.

Asthma is a complex trait for which different strategies have been used to identify its environmental and genetic predisposing factors. Here, we describe a novel methodological approach to select candidate genes for asthma genetic association studies. In this regard, the Genes to Diseases (G2D) computational tool has been used in combination with a genome-wide scan performed in a sub-sample of the Saguenay-Lac-St-Jean (SLSJ) asthmatic familial collection (n = 609) to identify candidate genes located in two suggestive loci shown to be linked with asthma (6q26) and atopy (10q26.3), and presenting differential parent-of-origin effects. This approach combined gene selection based on the G2D data mining analysis of the bibliographic and protein public databases, or according to the genes already known to be associated with the same or a similar phenotype. Ten genes (LPA, NOX3, SNX9, VIL2, VIP, ADAM8, DOCK1, FANK1, GPR123 and PTPRE) were selected for a subsequent association study performed in a large SLSJ sample (n = 1167) of individuals tested for asthma and atopy related phenotypes. Single nucleotide polymorphisms (n = 91) within the candidate genes were genotyped and analysed using a family-based association test. The results suggest a protective association to allergic asthma for PTPRE rs7081735 in the SLSJ sample (p = 0.000463; corrected p = 0.0478). This association has not been replicated in the Childhood Asthma Management Program (CAMP) cohort. Sequencing of the regions around rs7081735 revealed additional polymorphisms, but additional genotyping did not yield new associations. These results demonstrate that the G2D tool can be useful in the selection of candidate genes located in chromosomal regions linked to a complex trait.

Asthma genetics has been extensively studied and many genes have been associated with the development or severity of this disease. In contrast, the genetic basis of allergic rhinitis (AR) has not been evaluated as extensively. It is well known that asthma is closely related with AR since a large proportion of individuals with asthma also present symptoms of AR, and patients with AR have a 5-6 fold increased risk of developing asthma. Thus, the relevance of asthma candidate genes as predisposing factors for AR is worth investigating. The present study was designed to investigate if SNPs in highly replicated asthma genes are associated with the occurrence of AR.

Coronary artery disease (CAD) is one of the leading threats to global health. Previous research has proven that metabolic pathway disorders, such as high blood lipids and diabetes, are one of the risk factors that mostly cause CAD. However, the crosstalk between metabolic pathways and CAD was mostly studied on physiology processes by analyzing a single gene function. A canonical correlation analysis was used to identify the metabolic pathways, which were integrated as a unit to coexpress with CAD susceptibility genes, and to resolve additional metabolic factors that are related to CAD. Seven pathways, including citrate cycle, ubiquinone, terpenoid quinone biosynthesis, and N-glycan biosynthesis, were identified as an integrated unit coexpressed with CAD genes. These pathways could not be revealed as a coexpressed pathway through traditional methods as each single gene has weak correlation. Furthermore, sets of genes in these pathways were candidate markers for diagnosis and detection from patients' serum.

Microalgae have recently emerged as a key research topic, especially as biological models. Among them, the green alga Klebsormidium nitens, thanks to its particular adaptation to environmental stresses, represents an interesting photosynthetic eukaryote for studying the transition stages leading to the colonization of terrestrial life. The tolerance to different stresses is manifested by changes in gene expression, which can be monitored by quantifying the amounts of transcripts by RT-qPCR. The identification of optimal reference genes for experiment normalization was therefore necessary. In this study, using four statistical algorithms followed by the RankAggreg package, we determined the best reference gene pairs suitable for normalizing RT-qPCR data in K. nitens in response to three abiotic stresses: high salinity, PEG-induced dehydration and heat shock. Based on these reference genes, we were able to identify marker genes in response to the three abiotic stresses in K. nitens.

Mirtrons are alternative precursors for microRNA biogenesis that were recently described in invertebrates. These short hairpin introns use splicing to bypass Drosha cleavage, which is otherwise essential for the generation of canonical animal microRNAs. Using computational and experimental strategies, we now establish that mammals have mirtrons as well. We identified 3 mirtrons that are well conserved and expressed in diverse mammals, 16 primate-specific mirtrons, and 46 candidates supported by limited cloning evidence in primates. As with some fly and worm mirtrons, the existence of well-conserved mammalian mirtrons indicates their relatively ancient incorporation into endogenous regulatory pathways. However, as worms, flies, and mammals each have different sets of mirtrons, we hypothesize that different animals may have independently evolved the capacity for this hybrid small RNA pathway. This notion is supported by our observation of several clade-specific features of mammalian and invertebrate mirtrons.

Development in genetic technology has led to the identification of an increasing number of genes associated with epilepsy. These discoveries will both provide the basis for including genetic tests in clinical practice and improve diagnosis and treatment of epilepsy. By searching through several databases (OMIM, HGMD, and EpilepsyGene) and recent publications on PubMed, we found 977 genes that are associated with epilepsy. We classified these genes into 4 categories according to the manifestation of epilepsy in phenotypes. We found 84 genes that are considered as epilepsy genes: genes that cause epilepsies or syndromes with epilepsy as the core symptom. 73 genes were listed as neurodevelopment-associated genes: genes associated with both brain-development malformations and epilepsy. Several genes (536) were epilepsy-related: genes associated with both physical or other systemic abnormalities and epilepsy or seizures. We found 284 additional genes putatively associated with epilepsy; this requires further verification. These integrated data will provide new insights useful for both including genetic tests in the clinical practice and evaluating the results of genetic tests. We also summarized the epilepsy-associated genes according to their function, with the goal to better characterize the association between genes and epilepsies and to further understand the mechanisms underlying epilepsy.

Hepatocellular carcinoma (HCC) is the most common lethal malignancy of the liver worldwide. Thus, it is important to dig the key genes for uncovering the molecular mechanisms and to improve diagnostic and therapeutic options for HCC. This study aimed to encompass a set of statistical and machine learning computational approaches for identifying the key candidate genes for HCC. Three microarray datasets were used in this work, which were downloaded from the Gene Expression Omnibus Database. At first, normalization and differentially expressed genes (DEGs) identification were performed using limma for each dataset. Then, support vector machine (SVM) was implemented to determine the differentially expressed discriminative genes (DEDGs) from DEGs of each dataset and select overlapping DEDGs genes among identified three sets of DEDGs. Enrichment analysis was performed on common DEDGs using DAVID. A protein-protein interaction (PPI) network was constructed using STRING and the central hub genes were identified depending on the degree, maximum neighborhood component (MNC), maximal clique centrality (MCC), centralities of closeness, and betweenness criteria using CytoHubba. Simultaneously, significant modules were selected using MCODE scores and identified their associated genes from the PPI networks. Moreover, metadata were created by listing all hub genes from previous studies and identified significant meta-hub genes whose occurrence frequency was greater than 3 among previous studies. Finally, six key candidate genes (TOP2A, CDC20, ASPM, PRC1, NUSAP1, and UBE2C) were determined by intersecting shared genes among central hub genes, hub module genes, and significant meta-hub genes. Two independent test datasets (GSE76427 and TCGA-LIHC) were utilized to validate these key candidate genes using the area under the curve. Moreover, the prognostic potential of these six key candidate genes was also evaluated on the TCGA-LIHC cohort using survival analysis.

RNA sequencing allows the measuring of gene expression at a resolution unmet by expression arrays or RT-qPCR. It is however necessary to normalize sequencing data by library size, transcript size and composition, among other factors, before comparing expression levels. The use of internal control genes or spike-ins is advocated in the literature for scaling read counts, but the methods for choosing reference genes are mostly targeted at RT-qPCR studies and require a set of pre-selected candidate controls or pre-selected target genes.

Obesity and its associated metabolic syndrome are a leading cause of morbidity and mortality. Given the disease's heavy burden on patients and the healthcare system, there has been increased interest in identifying pharmacological targets for the treatment and prevention of obesity. Towards this end, genome-wide association studies (GWAS) have identified hundreds of human genetic variants associated with obesity. The next challenge is to experimentally define which of these variants are causally linked to obesity, and could therefore become targets for the treatment or prevention of obesity. Here we employ high-throughput in vivo RNAi screening to test for causality 293 C. elegans orthologs of human obesity-candidate genes reported in GWAS. We RNAi screened these 293 genes in C. elegans subject to two different feeding regimens: (1) regular diet, and (2) high-fructose diet, which we developed and present here as an invertebrate model of diet-induced obesity (DIO). We report 14 genes that promote obesity and 3 genes that prevent DIO when silenced in C. elegans. Further, we show that knock-down of the 3 DIO genes not only prevents excessive fat accumulation in primary and ectopic fat depots but also improves the health and extends the lifespan of C. elegans overconsuming fructose. Importantly, the direction of the association between expression variants in these loci and obesity in mice and humans matches the phenotypic outcome of the loss-of-function of the C. elegans ortholog genes, supporting the notion that some of these genes would be causally linked to obesity across phylogeny. Therefore, in addition to defining causality for several genes so far merely correlated with obesity, this study demonstrates the value of model systems compatible with in vivo high-throughput genetic screening to causally link GWAS gene candidates to human diseases.

Microtia is a congenital malformation of the external ear caused by genetic and/or environmental factors. However, no causal genetic mutations have been identified in isolated microtia patients. In this study, we utilized targeted genomic capturing combined with next-generation sequencing to screen for mutations in 307 deafness genes in 32 microtia patients. Forty-two rare heterozygous mutations in 25 genes, including 22 novel mutations in 24 isolated unilateral microtia cases were identified. Pathway analysis found five pathways especially focal adhesion pathway and ECM-receptor interaction pathway were significantly associated with microtia. The low-frequency variants association study was used and highlighted several strong candidate genes MUC4, MUC6, COL4A4, MYO7A, AKAP12, COL11A1, DSPP, ESPN, GPR98, PCDH15, BSN, CACNA1D, TPRN, and USH1C for microtia (P = 2.51 × 10-4). Among these genes, COL4A4 and COL11A1 may lead to microtia through focal adhesion pathway and ECM-receptor interaction pathway which are connected to the downstream Wnt signaling pathway. The present results indicate that certain genes may affect both external/middle and inner ear development, and demonstrate the benefits of using a capture array in microtia patients.