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Simple Summary: Plants are subjected to various environmental stresses that negatively impact growth and development and limit crop productivity. Therefore, in order to meet the requirements of the growing world population and food security, it is essential to develop cultivars resistant to abiotic stresses. In recent years, with the availability of genetic databases and the advancement in genome editing techniques, it is feasible to edit target genes with precision and create new opportunities for crop improvement that conventional breeding methods could not achieve. The genome-editing method using CRISPR-Cas systems is very powerful and confers exceptional versatility to develop improved cultivars at abiotic stresses. These efficient gene editing techniques facilitate the cultivation of superior-performing genotypes in challenging environmental conditions without compromising yield. Abiotic stresses extensively reduce agricultural crop production globally. Traditional breeding technology has been the fundamental approach used to cope with abiotic stresses. The development of gene editing technology for modifying genes responsible for the stresses and the related genetic networks has established the foundation for sustainable agriculture against environmental stress. Integrated approaches based on functional genomics and transcriptomics are now expanding the opportunities to elucidate the molecular mechanisms underlying abiotic stress responses. This review summarizes some of the features and weblinks of plant genome databases related to abiotic stress genes utilized for improving crops. The gene-editing tool based on clustered, regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) has revolutionized stress tolerance research due to its simplicity, versatility, adaptability, flexibility, and broader applications. However, off-target and low cleavage efficiency hinder the successful application of CRISPR/Cas systems. Computational tools have been developed for designing highly competent gRNA with better cleavage efficiency. This powerful genome editing tool offers tremendous crop improvement opportunities, overcoming conventional breeding techniques' shortcomings. Furthermore, we also discuss the mechanistic insights of the CRISPR/Cas9-based genome editing technology. This review focused on the current advances in understanding plant species' abiotic stress response mechanism and applying the CRISPR/Cas system genome editing technology to develop crop resilience against drought, salinity, temperature, heavy metals, and herbicides. [ABSTRACT FROM AUTHOR]

Microbial genome web portals have a broad range of capabilities that address a number of information-finding and analysis needs for scientists. This article compares the capabilities of the major microbial genome web portals to aid researchers in determining which portal(s) are best suited to their needs. We assessed both the bioinformatics tools and the data content of BioCyc, KEGG, Ensembl Bacteria, KBase, IMG, and PATRIC. For each portal, our assessment compared and tallied the available capabilities. The strengths of BioCyc include its genomic and metabolic tools, multi-search capabilities, table-based analysis tools, regulatory network tools and data, omics data analysis tools, breadth of data content, and large amount of curated data. The strengths of KEGG include its genomic and metabolic tools. The strengths of Ensembl Bacteria include its genomic tools and large number of genomes. The strengths of KBase include its genomic tools and metabolic models. The strengths of IMG include its genomic tools, multi-search capabilities, large number of genomes, table-based analysis tools, and breadth of data content. The strengths of PATRIC include its large number of genomes, table-based analysis tools, metabolic models, and breadth of data content.

The development of bioinformatic solutions is guided by biological knowledge of the subject. In some cases, we use unambiguous biological models, while in others we rely on assumptions. A commonly used assumption for genomes is that related species have similar genome sequences. This is even more obvious in the case of chloroplast genomes due to their slow evolution. We investigated whether the lengths of complete chloroplast sequences are closely related to the taxonomic proximity of the species. The study was performed using all available RefSeq sequences from the asterid and rosid clades. In general, chloroplast length distributions are narrow at both the family and genus levels. In addition, clear biological explanations have already been reported for families and genera that exhibit particularly wide distributions. The main factors responsible for the length variations are parasitic life forms, IR loss, IR expansions and contractions, and polyphyly. However, the presence of outliers in the distribution at the genus level is a strong indication of possible inaccuracies in sequence assembly. [ABSTRACT FROM AUTHOR]

The human gut holds a special place in the study of different microbial environments due to growing evidence that the gut microbiota is related to host health. However, despite extensive research, there is still a lack of knowledge about the core taxa forming the gut microbiota and, moreover, available information is biased towards western microbiomes in both genome databases and most core taxa studies. To tackle these limitations, we tested a database enrichment strategy and analyzed public datasets of whole-genome shotgun data, generated from 545 fecal samples, comprising three gradients of westernization. The NT database was selected as a baseline of biological diversity, subsequently being combined with various studies of interest related to the human microbiota. This enrichment strategy made it possible to improve classification capacity, compared to the original unenriched database, regarding the various lifestyles and populations studied. The effects of incomplete-taxonomy metagenome-assembled genomes on genome database enrichment were also examined, revealing that, while they are helpful, they should be used with caution depending on the taxonomic level of interest. Moreover, in terms of high prevalence, the core analysis revealed a conserved set of bacterial taxa in the healthy human gut microbiota worldwide, despite apparent lifestyle differences. Such taxa show a set of traits, metabolic roles, and ancestral status, making them suitable candidates for a hypothetical phylogenetic core of mutualistic microorganisms co-evolving with the human species.

The development of bioinformatic solutions is guided by biological knowledge of the subject. In some cases, we use unambiguous biological models, while in others we rely on assumptions. A commonly used assumption for genomes is that related species have similar genome sequences. This is even more obvious in the case of chloroplast genomes due to their slow evolution. We investigated whether the lengths of complete chloroplast sequences are closely related to the taxonomic proximity of the species. The study was performed using all available RefSeq sequences from the asterid and rosid clades. In general, chloroplast length distributions are narrow at both the family and genus levels. In addition, clear biological explanations have already been reported for families and genera that exhibit particularly wide distributions. The main factors responsible for the length variations are parasitic life forms, IR loss, IR expansions and contractions, and polyphyly. However, the presence of outliers in the distribution at the genus level is a strong indication of possible inaccuracies in sequence assembly.

Pathogen detection, identification, and tracking is shifting from non-molecular methods, DNA fingerprinting methods, and single gene methods to methods relying on whole genomes. Viral Ebola and influenza genome data are being used for real-time tracking, while food-borne bacterial pathogen outbreaks and hospital outbreaks are investigated using whole genomes in the UK, Canada, the USA and the other countries. Also, plant pathogen genomes are starting to be used to investigate plant disease epidemics such as the wheat blast outbreak in Bangladesh. While these genome-based approaches provide never-seen advantages over all previous approaches with regard to public health and biosecurity, they also come with new vulnerabilities and risks with regard to cybersecurity. The more we rely on genome databases, the more likely these databases will become targets for cyber-attacks to interfere with public health and biosecurity systems by compromising their integrity, taking them hostage, or manipulating the data they contain. Also, while there is the potential to collect pathogen genomic data from infected individuals or agricultural and food products during disease outbreaks to improve disease modeling and forecast, how to protect the privacy of individuals, growers, and retailers is another major cyberbiosecurity challenge. As data become linkable to other data sources, individuals and groups become identifiable and potential malicious activities targeting those identified become feasible. Here, we define a number of potential cybersecurity weaknesses in today's pathogen genome databases to raise awareness, and we provide potential solutions to strengthen cyberbiosecurity during the development of the next generation of pathogen genome databases.

Microbial genome web portals have a broad range of capabilities that address a number of information-finding and analysis needs for scientists. This article compares the capabilities of the major microbial genome web portals to aid researchers in determining which portal(s) are best suited to their needs. We assessed both the bioinformatics tools and the data content of BioCyc, KEGG, Ensembl Bacteria, KBase, IMG, and PATRIC. For each portal, our assessment compared and tallied the available capabilities. The strengths of BioCyc include its genomic and metabolic tools, multi-search capabilities, table-based analysis tools, regulatory network tools and data, omics data analysis tools, breadth of data content, and large amount of curated data. The strengths of KEGG include its genomic and metabolic tools. The strengths of Ensembl Bacteria include its genomic tools and large number of genomes. The strengths of KBase include its genomic tools and metabolic models. The strengths of IMG include its genomic tools, multi-search capabilities, large number of genomes, table-based analysis tools, and breadth of data content. The strengths of PATRIC include its large number of genomes, table-based analysis tools, metabolic models, and breadth of data content.

BioCyc.org is a microbial genome Web portal that combines thousands of genomes with additional information inferred by computer programs, imported from other databases and curated from the biomedical literature by biologist curators. BioCyc also provides an extensive range of query tools, visualization services and analysis software. Recent advances in BioCyc include an expansion in the content of BioCyc in terms of both the number of genomes and the types of information available for each genome; an expansion in the amount of curated content within BioCyc; and new developments in the BioCyc software tools including redesigned gene/protein pages and metabolite pages; new search tools; a new sequence-alignment tool; a new tool for visualizing groups of related metabolic pathways; and a facility called SmartTables, which enables biologists to perform analyses that previously would have required a programmer's assistance. [ABSTRACT FROM AUTHOR]

Abstract The sequence of the human genome provides a scaffold on which numerous annotations, such the locations of genes, can be laid. Genome browsers have been created to allow the simultaneous display of multiple annotations within a graphical interface. In addition, they provide the ability to search for markers and sequences, to extract annotations for specific regions or for the whole genome and to act as a central starting point for genomic research. This review describes the basic functionality of genome browsers and compares three of them: the University of California Santa Cruz (UCSC) Genome Browser, the Ensembl Genome Browser and the NCBI MapViewer.

Viral metagenomics enables the detection, characterization, and quantification of viral sequences present in shotgun-sequenced datasets of purified virus-like particles and whole metagenomes. Next generation sequencing (Illumina) derived short single or paired-end read runs are a principal platform for metagenomics, and assembly of short reads allows for the identification of distinguishing viral signatures and complex genomic features for taxonomy and functional annotation. Here we describe the identification and characterization of viral genome sequences, bacteriophages, and eukaryotic viruses, from a cohort of human stool samples, using multiple methods. Following the purification of virus-like particles, sequencing, quality refinement, and genome assembly, we begin the protocol with raw short reads deposited in an open-source nucleotide archive. We highlight the use of VIBRANT, an automated computational tool for the characterization of microbial viruses and their viral community function. Finally, we also describe an alternative assembly-free option of mapping reads to established databases of reference genomes and previously characterized metagenome-assembled viral genomes., (© 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Extensive studies on floral transition in model species have revealed a network of regulatory interactions between proteins that transduce and integrate developmental and environmental signals to promote or inhibit the transition to flowering. Previous studies indicated FLOWERING PROMOTING FACTOR 1 (FPF1) gene was involved in the promotion of flowering, but the molecular mechanism was still unclear. Here, FPF1 homologous sequences were screened from diploid Gossypium raimondii L. (D-genome, n = 13) and Gossypium arboreum L. genome (A-genome, n = 13) databases. Orthologous genes from the two species were compared, suggesting that distinctions at nucleic acid and amino acid levels were not equivalent because of codon degeneracy. Six FPF1 homologous genes were identified from the cultivated allotetraploid Gossypium hirsutum L. (AD-genome, n = 26). Analysis of relative transcripts of the six genes in different tissues revealed that this gene family displayed strong tissue-specific expression. GhFPF1, encoding a 12.0-kDa protein (Accession No: KC832319) exerted more transcripts in floral apices of short-season cotton, hinting that it could be involved in floral regulation. Significantly activated APETALA 1 and suppressed FLOWERING LOCUS C expression were induced by over-expression of GhFPF1 in the Arabidopsis Columbia-0 ecotype. In addition, transgenic Arabidopsis displayed a constitutive shade-avoiding phenotype that is characterized by long hypocotyls and petioles, reduced chlorophyll content, and early flowering. We propose that GhFPF1 may be involved in flowering time control and shade-avoidance responses. [ABSTRACT FROM AUTHOR]

Bacterial genome annotations are accumulating rapidly in the GenBank database and the use of automated annotation technologies to create these annotations has become the norm. However, these automated methods commonly result in a small, but significant percentage of genome annotation errors. To improve accuracy and reliability, we analyzed the Caulobacter crescentus NA1000 genome utilizing computer programs Artemis and MICheck to manually examine the third codon position GC content, alignment to a third codon position GC frame plot peak, and matches in the GenBank database. We identified 11 new genes, modified the start site of 113 genes, and changed the reading frame of 38 genes that had been incorrectly annotated. Furthermore, our manual method of identifying protein-coding genes allowed us to remove 112 non-coding regions that had been designated as coding regions. The improved NA1000 genome annotation resulted in a reduction in the use of rare codons since noncoding regions with atypical codon usage were removed from the annotation and 49 new coding regions were added to the annotation. Thus, a more accurate codon usage table was generated as well. These results demonstrate that a comparison of the location of peaks third codon position GC content to the location of protein coding regions could be used to verify the annotation of any genome that has a GC content that is greater than 60%. [ABSTRACT FROM AUTHOR]

Time-course gene expression datasets, which record continuous biological processes of genes, have recently been used to predict gene function. However, only few positive genes can be obtained from annotation databases, such as gene ontology (GO). To obtain more useful information and effectively predict gene function, gene annotations are clustered together to form a learnable and effective learning system. In this paper, we propose a novel multi-instance hierarchical clustering (MIHC) method to establish a learning system by clustering GO and compare this method with other learning system establishment methods. Multi-label support vector machine classifier and multi-label K-nearest neighbor classifier are used to verify these methods in four yeast time-course gene expression datasets. The MIHC method shows good performance, which serves as a guide to annotators or refines the annotation in detail. [ABSTRACT FROM AUTHOR]

Fungi are a large, complex group, increasingly recognized as emerging threats. Their roles as modifiers of health mandate accurate portrayals of fungal communities in humans. As an entry point into the airways and gastrointestinal tract, fungi in the mouth are relevant to several biocompartments. We have revised current practices in sequence-based taxonomy assignments and employed the improvements to address the question of the fungal genera present in the healthy human mouth. The human oral mycobiome was surveyed using massively parallel, high throughput sequencing of internal transcribed spacer 1 (ITS1) amplicons from saliva following robust extraction methods. Taxonomy was assigned by comparison to a curated reference dataset, followed by filtering with an empirically determined BLAST E-value match statistic (10−42). Nomenclature corrections further refined results by conjoining redundant names for a single fungal genus. Following these curation steps, about two-thirds of the initially identified genera were eliminated. In comparison with the one similar metagenomic study and several earlier culture-based ones, our findings change the current conception of the oral mycobiome, especially with the discovery of the high prevalence and abundance of the genus Malassezia. Previously identified as an important pathogen of the skin, and recently reported as the predominant fungal genus at the nostril and backs of the head and ear, this is the first account of Malassezia in the human mouth. Findings from this study were in good agreement with others on the existence of many consensus members of the core mycobiome, and on unique patterns for individual subjects. This research offered a cautionary note about unconditional acceptance of lengthy lists of community members produced by automated assignments, provided a roadmap for enhancing the likely biological relevance of sequence-based fungal surveys, and built the foundation for understanding the role of fungi in health and disease of the oral cavity. [ABSTRACT FROM AUTHOR]

Background: Transposable elements (TEs) are the most abundant genomic components in eukaryotes and affect the genome by their replications and movements to generate genetic plasticity. Sweet potato performs asexual reproduction generally and the TEs may be an important genetic factor for genome reorganization. Complete identification of TEs is essential for the study of genome evolution. However, the TEs of sweet potato are still poorly understood because of its complex hexaploid genome and difficulty in genome sequencing. The recent availability of the sweet potato transcriptome databases provides an opportunity for discovering and characterizing the expressed TEs. Methodology/Principal Findings: We first established the integrated-transcriptome database by de novo assembling four published sweet potato transcriptome databases from three cultivars in China. Using sequence-similarity search and analysis, a total of 1,405 TEs including 883 retrotransposons and 522 DNA transposons were predicted and categorized. Depending on mapping sets of RNA-Seq raw short reads to the predicted TEs, we compared the quantities, classifications and expression activities of TEs inter- and intra-cultivars. Moreover, the differential expressions of TEs in seven tissues of Xushu 18 cultivar were analyzed by using Illumina digital gene expression (DGE) tag profiling. It was found that 417 TEs were expressed in one or more tissues and 107 in all seven tissues. Furthermore, the copy number of 11 transposase genes was determined to be 1–3 copies in the genome of sweet potato by Real-time PCR-based absolute quantification. Conclusions/Significance: Our result provides a new method for TE searching on species with transcriptome sequences while lacking genome information. The searching, identification and expression analysis of TEs will provide useful TE information in sweet potato, which are valuable for the further studies of TE-mediated gene mutation and optimization in asexual reproduction. It contributes to elucidating the roles of TEs in genome evolution. [ABSTRACT FROM AUTHOR]

Microarray databases are a large source of genetic data, which, upon proper analysis, could enhance our understanding of biology and medicine. Many microarray experiments have been designed to investigate the genetic mechanisms of cancer, and analytical approaches have been applied in order to classify different types of cancer or distinguish between cancerous and non-cancerous tissue. However, microarrays are high-dimensional datasets with high levels of noise and this causes problems when using machine learning methods. A popular approach to this problem is to search for a set of features that will simplify the structure and to some degree remove the noise from the data. The most widely used approach to feature extraction is principal component analysis (PCA) which assumes a multivariate Gaussian model of the data. More recently, non-linear methods have been investigated. Among these, manifold learning algorithms, for example Isomap, aim to project the data from a higher dimensional space onto a lower dimension one. We have proposed a priori manifold learning for finding a manifold in which a representative set of microarray data is fused with relevant data taken from the KEGG pathway database. Once the manifold has been constructed the raw microarray data is projected onto it and clustering and classification can take place. In contrast to earlier fusion based methods, the prior knowledge from the KEGG databases is not used in, and does not bias the classification process—it merely acts as an aid to find the best space in which to search the data. In our experiments we have found that using our new manifold method gives better classification results than using either PCA or conventional Isomap. [ABSTRACT FROM AUTHOR]

Background: Meta-analysis of gene expression array databases has the potential to reveal information about gene function. The identification of gene-gene interactions may be inferred from gene expression information but such meta-analysis is often limited to a single microarray platform. To address this limitation, we developed a gene-centered approach to analyze differential expression across thousands of gene expression experiments and created the CO-Regulation Database (CORD) to determine which genes are correlated with a queried gene. Results: Using the GEO and ArrayExpress database, we analyzed over 120,000 group by group experiments from gene microarrays to determine the correlating genes for over 30,000 different genes or hypothesized genes. CORD output data is presented for sample queries with focus on genes with well-known interaction networks including p16 (CDKN2A), vimentin (VIM), MyoD (MYOD1). CDKN2A, VIM, and MYOD1 all displayed gene correlations consistent with known interacting genes. Conclusions: We developed a facile, web-enabled program to determine gene-gene correlations across different gene expression microarray platforms. Using well-characterized genes, we illustrate how CORD's identification of co-expressed genes contributes to a better understanding a gene's potential function. The website is found at http://cord-db.org. [ABSTRACT FROM AUTHOR]

The availability of many complete, annotated proteomes enables the systematic study of the relationships between protein conservation and functionality. We explore this question based solely on the presence or absence of protein homologues (a.k.a. conservation profiles). We study 18 metazoans, from two distinct points of view: the human's and the fly's. Using the GOrilla gene ontology (GO) analysis tool, we explore functional enrichment of the “universal proteins”, those with homologues in all 17 other species, and of the “non-universal proteins”. A large number of GO terms are strongly enriched in both human and fly universal proteins. Most of these functions are known to be essential. A smaller number of GO terms, exhibiting markedly different properties, are enriched in both human and fly non-universal proteins. We further explore the non-universal proteins, whose conservation profiles are consistent with the “tree of life” (TOL consistent), as well as the TOL inconsistent proteins. Finally, we applied Quantum Clustering to the conservation profiles of the TOL consistent proteins. Each cluster is strongly associated with one or a small number of specific monophyletic clades in the tree of life. The proteins in many of these clusters exhibit strong functional enrichment associated with the “life style” of the related clades. Most previous approaches for studying function and conservation are “bottom up”, studying protein families one by one, and separately assessing the conservation of each. By way of contrast, our approach is “top down”. We globally partition the set of all proteins hierarchically, as described above, and then identify protein families enriched within different subdivisions. While supporting previous findings, our approach also provides a tool for discovering novel relations between protein conservation profiles, functionality, and evolutionary history as represented by the tree of life. [ABSTRACT FROM AUTHOR]

There is an acute need for better tools to extract knowledge from the growing flood of sequence data. For example, thousands of complete genomes have been sequenced, and their metabolic networks inferred. Such data should enable a better understanding of evolution. However, most existing network analysis methods are based on pair-wise comparisons, and these do not scale to thousands of genomes. Here we propose the use of weighted graphs as a data structure to enable large-scale phylogenetic analysis of networks. We have developed three types of weighted graph for enzymes: taxonomic (these summarize phylogenetic importance), isoenzymatic (these summarize enzymatic variety/redundancy), and sequence-similarity (these summarize sequence conservation); and we applied these types of weighted graph to survey prokaryotic metabolism. To demonstrate the utility of this approach we have compared and contrasted the large-scale evolution of metabolism in Archaea and Eubacteria. Our results provide evidence for limits to the contingency of evolution. [ABSTRACT FROM AUTHOR]

Genome-Wide Association Studies are widely used to correlate phenotypic traits with genetic variants. These studies usually compare the genetic variation between two groups to single out certain Single Nucleotide Polymorphisms (SNPs) that are linked to a phenotypic variation in one of the groups. However, it is necessary to have a large enough sample size to find statistically significant correlations. Direct-To-Consumer (DTC) genetic testing can supply additional data: DTC-companies offer the analysis of a large amount of SNPs for an individual at low cost without the need to consult a physician or geneticist. Over 100,000 people have already been genotyped through Direct-To-Consumer genetic testing companies. However, this data is not public for a variety of reasons and thus cannot be used in research. It seems reasonable to create a central open data repository for such data. Here we present the web platform openSNP, an open database which allows participants of Direct-To-Consumer genetic testing to publish their genetic data at no cost along with phenotypic information. Through this crowdsourced effort of collecting genetic and phenotypic information, openSNP has become a resource for a wide area of studies, including Genome-Wide Association Studies. openSNP is hosted at http://www.opensnp.org, and the code is released under MIT-license at http://github.com/gedankenstuecke/snpr. [ABSTRACT FROM AUTHOR]

Extensive studies on floral transition in model species have revealed a network of regulatory interactions between proteins that transduce and integrate developmental and environmental signals to promote or inhibit the transition to flowering. Previous studies indicated FLOWERING PROMOTING FACTOR 1 (FPF1) gene was involved in the promotion of flowering, but the molecular mechanism was still unclear. Here, FPF1 homologous sequences were screened from diploid Gossypium raimondii L. (D-genome, n = 13) and Gossypium arboreum L. genome (A-genome, n = 13) databases. Orthologous genes from the two species were compared, suggesting that distinctions at nucleic acid and amino acid levels were not equivalent because of codon degeneracy. Six FPF1 homologous genes were identified from the cultivated allotetraploid Gossypium hirsutum L. (AD-genome, n = 26). Analysis of relative transcripts of the six genes in different tissues revealed that this gene family displayed strong tissue-specific expression. GhFPF1, encoding a 12.0-kDa protein (Accession No: KC832319) exerted more transcripts in floral apices of short-season cotton, hinting that it could be involved in floral regulation. Significantly activated APETALA 1 and suppressed FLOWERING LOCUS C expression were induced by over-expression of GhFPF1 in the Arabidopsis Columbia-0 ecotype. In addition, transgenic Arabidopsis displayed a constitutive shade-avoiding phenotype that is characterized by long hypocotyls and petioles, reduced chlorophyll content, and early flowering. We propose that GhFPF1 may be involved in flowering time control and shade-avoidance responses. [ABSTRACT FROM AUTHOR]

Background: Transposable elements (TEs) are the most abundant genomic components in eukaryotes and affect the genome by their replications and movements to generate genetic plasticity. Sweet potato performs asexual reproduction generally and the TEs may be an important genetic factor for genome reorganization. Complete identification of TEs is essential for the study of genome evolution. However, the TEs of sweet potato are still poorly understood because of its complex hexaploid genome and difficulty in genome sequencing. The recent availability of the sweet potato transcriptome databases provides an opportunity for discovering and characterizing the expressed TEs. Methodology/Principal Findings: We first established the integrated-transcriptome database by de novo assembling four published sweet potato transcriptome databases from three cultivars in China. Using sequence-similarity search and analysis, a total of 1,405 TEs including 883 retrotransposons and 522 DNA transposons were predicted and categorized. Depending on mapping sets of RNA-Seq raw short reads to the predicted TEs, we compared the quantities, classifications and expression activities of TEs inter- and intra-cultivars. Moreover, the differential expressions of TEs in seven tissues of Xushu 18 cultivar were analyzed by using Illumina digital gene expression (DGE) tag profiling. It was found that 417 TEs were expressed in one or more tissues and 107 in all seven tissues. Furthermore, the copy number of 11 transposase genes was determined to be 1–3 copies in the genome of sweet potato by Real-time PCR-based absolute quantification. Conclusions/Significance: Our result provides a new method for TE searching on species with transcriptome sequences while lacking genome information. The searching, identification and expression analysis of TEs will provide useful TE information in sweet potato, which are valuable for the further studies of TE-mediated gene mutation and optimization in asexual reproduction. It contributes to elucidating the roles of TEs in genome evolution. [ABSTRACT FROM AUTHOR]

The development of chronic obstructive pulmonary disease, upon exposure to tobacco smoke, is the cumulative effect of defects in several genes. With the aim of understanding the genetic structure that is characteristic of our patient population, we selected forty two single nucleotide polymorphisms of twenty genes based on previous studies and genotyped a total of 382 samples, which included 236 patients and 146 controls using Sequenom MassARRAY system. Allele frequencies of rs2276109 (MMP12) and rs1800925 (IL13) differed significantly between patients and controls (p = 0.013 and 0.044 respectively). Genotype analysis showed association of rs2276109 (MMP12) under additive and dominant models (p = 0.017, p = 0.012 respectively), rs1800925 (IL13) under additive model (p = 0.047) and under recessive model, rs1695 (GSTP1; p = 0.034), rs729631, rs975278, rs7583463 (SERPINE2; p = 0.024, 0.024 and 0.012 respectively), rs2568494, rs10851906 (IREB2; p = 0.026 and 0.041 respectively) and rs7671167 (FAM13A; p = 0.029). The minor alleles of rs1695 (G), rs7671167 (T), rs729631 (G), rs975278 (A) and rs7583463 (A) showed significant negative association whereas those of rs2276109 (G), rs2568494 (A), rs10851906 (G) and rs1800469 (T; TGF-β) showed significant positive association with lung function under different genetic models. Haplotypes carrying A allele of rs2276109, G allele of rs1695 showed negative correlation with lung function. Haplotypes carrying major alleles of rs7671167 (C) of FAM13A and rs729631 (C), rs975278 (G), rs7583463 (C) of SERPINE2 had protective effect on lung function. Haplotypes of IREB2 carrying major alleles of rs2568494 (G), rs2656069 (A), rs10851906 (A), rs965604 (C) and minor alleles of rs1964678 (T), rs12593229 (T) showed negative correlation with lung function. In conclusion, our study replicated the results of most of the previous studies. However, the positive correlation between the minor alleles of rs2568494 (A) and rs10851906 (G) of IREB2 and lung function needs further investigation. [ABSTRACT FROM AUTHOR]

With the exponential increase in the number of sequenced organisms, automated annotation of proteins is becoming increasingly important. Intrinsically disordered regions are known to play a significant role in protein function. Despite their abundance, especially in eukaryotes, they are rarely used to inform function prediction systems. In this study, we extracted seven sequence features in intrinsically disordered regions and developed a scheme to use them to predict Gene Ontology Slim terms associated with proteins. We evaluated the function prediction performance of each feature. Our results indicate that the residue composition based features have the highest precision while bigram probabilities, based on sequence profiles of intrinsically disordered regions obtained from PSIBlast, have the highest recall. Amino acid bigrams and features based on secondary structure show an intermediate level of precision and recall. Almost all features showed a high prediction performance for GO Slim terms related to extracellular matrix, nucleus, RNA and DNA binding. However, feature performance varied significantly for different GO Slim terms emphasizing the need for a unique classifier optimized for the prediction of each functional term. These findings provide a first comprehensive and quantitative evaluation of sequence features in intrinsically disordered regions and will help in the development of a more informative protein function predictor. [ABSTRACT FROM AUTHOR]

Two-component signal transduction systems are commonly composed of a sensor histidine kinase and a cognate response regulator, modulating gene expression in response to environmental changes through a phosphorylation-dependent process. CosR is an OmpR-type response regulator essential for the viability of Campylobacter jejuni, a major foodborne pathogenic species causing human gastroenteritis. Although CosR is a response regulator, its cognate sensor kinase has not been identified in C. jejuni. In this study, DNA sequence analysis of the cosR flanking regions revealed that a gene encoding a putative sensor kinase, which we named cosS, is prevalent in non-thermotolerant Campylobacter spp., but not in thermotolerant campylobacters. Phosphorylation assays indicated that C. fetus CosS rapidly autophosphorylates and then phosphorylates C. fetus CosR, suggesting that the CosRS system constitutes a paired two-component signal transduction system in C. fetus. However, C. fetus CosS does not phosphorylate C. jejuni CosR, suggesting that CosR may have different regulatory cascades between thermotolerant and non-thermotolerant Campylobacter species. Comparison of CosR homolog amino acid sequences showed that the conserved phosphorylation residue (D51), which is present in all non-thermotolerant Campylobacter spp., is absent from the CosR homologs of thermotolerant Campylobacter species. However, C. jejuni CosR was not phosphorylated by C. fetus CosS even after site-directed mutagenesis of N51D, implying that C. jejuni CosR may possibly function phosphorylation-independently. In addition, the results of cosS mutational analysis indicated that CosS is not associated with the temperature dependence of the Campylobacter spp. despite its unique divergent distribution only in non-thermotolerant campylobacters. The findings in this study strongly suggest that thermotolerant and non-thermotolerant Campylobacter spp. have different signal sensing mechanisms associated with the CosR regulation. [ABSTRACT FROM AUTHOR]

Transcriptomics meta-analysis aims at re-using existing data to derive novel biological hypotheses, and is motivated by the public availability of a large number of independent studies. Current methods are based on breaking down studies into multiple comparisons between phenotypes (e.g. disease vs. healthy), based on the studies' experimental designs, followed by computing the overlap between the resulting differential expression signatures. While useful, in this methodology each study yields multiple independent phenotype comparisons, and connections are established not between studies, but rather between subsets of the studies corresponding to phenotype comparisons. We propose a rank-based statistical meta-analysis framework that establishes global connections between transcriptomics studies without breaking down studies into sets of phenotype comparisons. By using a rank product method, our framework extracts global features from each study, corresponding to genes that are consistently among the most expressed or differentially expressed genes in that study. Those features are then statistically modelled via a term-frequency inverse-document frequency (TF-IDF) model, which is then used for connecting studies. Our framework is fast and parameter-free; when applied to large collections of Homo sapiens and Streptococcus pneumoniae transcriptomics studies, it performs better than similarity-based approaches in retrieving related studies, using a Medical Subject Headings gold standard. Finally, we highlight via case studies how the framework can be used to derive novel biological hypotheses regarding related studies and the genes that drive those connections. Our proposed statistical framework shows that it is possible to perform a meta-analysis of transcriptomics studies with arbitrary experimental designs by deriving global expression features rather than decomposing studies into multiple phenotype comparisons. [ABSTRACT FROM AUTHOR]

The temporal order of cancer gene mutations in tumors is essential for understanding and treating the disease. Existing methods are unable to infer the order of mutations that are identified at the same time in individual tumor samples, leaving the heterogeneity of the order unknown. Here, we show that through a complex network-based approach, which is based on the newly defined statistic –carcinogenesis information conductivity (CIC), the temporal order in individual samples can be effectively inferred. The results suggest that tumor-suppressor genes might more frequently initiate the order of mutations than oncogenes, and every type of cancer might have its own unique order of mutations. The initial mutations appear to be dedicated to acquiring the function of evading apoptosis, and some order constraints might reflect potential regularities. Our approach is completely data-driven without any parameter settings and can be expected to become more effective as more data will become available. [ABSTRACT FROM AUTHOR]

A broadly accepted and stable biological classification system is a prerequisite for biological sciences. It provides the means to describe and communicate about life without ambiguity. Current biological classification and nomenclature use the species as the basic unit and require lengthy and laborious species descriptions before newly discovered organisms can be assigned to a species and be named. The current system is thus inadequate to classify and name the immense genetic diversity within species that is now being revealed by genome sequencing on a daily basis. To address this lack of a general intra-species classification and naming system adequate for today’s speed of discovery of new diversity, we propose a classification and naming system that is exclusively based on genome similarity and that is suitable for automatic assignment of codes to any genome-sequenced organism without requiring any phenotypic or phylogenetic analysis. We provide examples demonstrating that genome similarity-based codes largely align with current taxonomic groups at many different levels in bacteria, animals, humans, plants, and viruses. Importantly, the proposed approach is only slightly affected by the order of code assignment and can thus provide codes that reflect similarity between organisms and that do not need to be revised upon discovery of new diversity. We envision genome similarity-based codes to complement current biological nomenclature and to provide a universal means to communicate unambiguously about any genome-sequenced organism in fields as diverse as biodiversity research, infectious disease control, human and microbial forensics, animal breed and plant cultivar certification, and human ancestry research. [ABSTRACT FROM AUTHOR]

Cystic fibrosis (CF) is caused by mutations in the cystic fibrosis transmembrane regulator gene (CFTR). In light of the strong allelic heterogeneity and regional specificity of the mutation spectrum, the strategy of molecular diagnostics and counseling in CF requires genetic tests to reflect the frequency profile characteristic for a given population. The goal of the study was to provide an updated comprehensive estimation of the distribution of CFTR mutations in Polish CF patients and to assess the effectiveness of INNOLiPA_CFTR tests in Polish population. The analyzed cohort consisted of 738 patients with the clinically confirmed CF diagnosis, prescreened for molecular defects using INNOLiPA_CFTR panels from Innogenetics. A combined efficiency of INNOLiPA CFTR_19 and CFTR_17_TnUpdate tests was 75.5%; both mutations were detected in 68.2%, and one mutation in 14.8% of the affected individuals. The group composed of all the patients with only one or with no mutation detected (109 and 126 individuals, respectively) was analyzed further using a mutation screening approach, i.e. SSCP/HD (single strand conformational polymorphism/heteroduplex) analysis of PCR products followed by sequencing of the coding sequence. As a result, 53 more mutations were found in 97 patients. The overall efficiency of the CF allele detection was 82.5% (7.0% increase compared to INNOLiPA tests alone). The distribution of the most frequent mutations in Poland was assessed. Most of the mutations repetitively found in Polish patients had been previously described in other European populations. The most frequent mutated allele, F508del, represented 54.5% of Polish CF chromosomes. Another eight mutations had frequencies over 1%, 24 had frequencies between 1 and 0.1%; c.2052-2053insA and c.3468+2_3468+3insT were the most frequent non-INNOLiPA mutations. Mutation distribution described herein is also relevant to the Polish diaspora. Our study also demonstrates that the reported efficiency of mutation detection strongly depends on the diagnostic experience of referring health centers. [ABSTRACT FROM AUTHOR]

Over 90% of the human listeriosis cases are caused by Listeria monocytogenes serotypes 1/2a, 1/2b and 4b strains. As an alternative to antigen-antibody based serotyping, a PCR-based method for serogrouping has been developed and validated. In this communication, we report an in-depth analysis of five 4b variant strains, four clinical isolates from Australia and one environmental isolate from USA. Although these five strains were serotype 4b by classical serotyping method, the serogrouping PCR profiles of these strains show the presence of a 1/2a-3a specific amplicon in addition to the standard 4b-4d-4e specific amplicons. These strains were further analyzed by pulsed field gel electrophoresis, binary gene typing, multi-locus variable-number-tandem-repeat analysis and a high density pan-genomic Listeria microarray. Using these sub-typing results, the clinical isolates were grouped into two distinct genomic groups- one of which could be part of an unidentified outbreak. The microarray results when compared with our database of other 4b outbreak isolates indicated that the serotype 4b variant strains represent very different genotypic profiles than the known reported 4b outbreak strains representing major epidemic clones. The acquisition of serotype 1/2a gene clusters by the 4b variant strains appears to be independent in origin, spanning large areas of geographical and temporal space and may indicate predisposition of some 4b strains towards accepting DNA from related organisms. [ABSTRACT FROM AUTHOR]

Transporters are essential in homeostatic exchange of endogenous and exogenous substances at the systematic, organic, cellular, and subcellular levels. Gene mutations of transporters are often related to pharmacogenetics traits. Recent developments in high throughput technologies on genomics, transcriptomics and proteomics allow in depth studies of transporter genes in normal cellular processes and diverse disease conditions. The flood of high throughput data have resulted in urgent need for an updated knowledgebase with curated, organized, and annotated human transporters in an easily accessible way. Using a pipeline with the combination of automated keywords query, sequence similarity search and manual curation on transporters, we collected 1,555 human non-redundant transporter genes to develop the Human Transporter Database (HTD) (http://htd.cbi.pku.edu.cn). Based on the extensive annotations, global properties of the transporter genes were illustrated, such as expression patterns and polymorphisms in relationships with their ligands. We noted that the human transporters were enriched in many fundamental biological processes such as oxidative phosphorylation and cardiac muscle contraction, and significantly associated with Mendelian and complex diseases such as epilepsy and sudden infant death syndrome. Overall, HTD provides a well-organized interface to facilitate research communities to search detailed molecular and genetic information of transporters for development of personalized medicine. [ABSTRACT FROM AUTHOR]

C+G content (GC content or G+C content) is known to be correlated with genome/chromosome size in bacteria but the relationship for other kingdoms remains unclear. This study analyzed genome size, chromosome size, and base composition in most of the available sequenced genomes in various kingdoms. Genome size tends to increase during evolution in plants and animals, and the same is likely true for bacteria. The genomic C+G contents were found to vary greatly in microorganisms but were quite similar within each animal or plant subkingdom. In animals and plants, the C+G contents are ranked as follows: monocot plants>mammals>non-mammalian animals>dicot plants. The variation in C+G content between chromosomes within species is greater in animals than in plants. The correlation between average chromosome C+G content and chromosome length was found to be positive in Proteobacteria, Actinobacteria (but not in other analyzed bacterial phyla), Ascomycota fungi, and likely also in some plants; negative in some animals, insignificant in two protist phyla, and likely very weak in Archaea. Clearly, correlations between C+G content and chromosome size can be positive, negative, or not significant depending on the kingdoms/groups or species. Different phyla or species exhibit different patterns of correlation between chromosome-size and C+G content. Most chromosomes within a species have a similar pattern of variation in C+G content but outliers are common. The data presented in this study suggest that the C+G content is under genetic control by both trans- and cis- factors and that the correlation between C+G content and chromosome length can be positive, negative, or not significant in different phyla. [ABSTRACT FROM AUTHOR]

Background: Polymorphisms at cleavage sites (CS) can influence Gag and Pol proteins processing by the viral protease (PR), restore viral fitness and influence the virological outcome of specific antiretroviral drugs. However, data of HIV-1 variant-associated CS variability is scarce. Methods: In this descriptive research, we examine the effect of HIV-1 variants on CS conservation using all 9,028 gag and 3,906 pol HIV-1 sequences deposited in GenBank, focusing on the 110 residues (10 per site) involved at 11 CS: P17/P24, P24/P2, P2/P7, P7/P1, P1/P6gag, NC/TFP, TFP/P6pol, P6pol/PR, PR/RTp51, RTp51/RTp66 and RTp66/IN. CS consensus amino acid sequences across HIV-1 groups (M, O, N, P), group M 9 subtypes and 51 circulating recombinant forms (CRF) were inferred from our alignments and compared to the HIV-1 consensus-of-consensuses sequence provided by GenBank. Results: In all HIV-1 variants, the most conserved CS were PR/RTp51, RTp51/RTp66, P24/P2 and RTp66/IN and the least P2/P7 and P6pol/PR. Conservation was significantly lower in subtypes vs. recombinants in P2/P7 and TFP/P6pol and higher in P17/P24. We found a significantly higher conservation rate among Group M vs. non-M Groups HIV-1. The late processing sites at Gag (P7/P1) and GagPol precursors (PR/RTp51) presented a significantly higher conservation vs. the first CS (P2/P7) in the 4 HIV-1 groups. Here we show 52 highly conserved residues across HIV-1 variants in 11 CS and the amino acid consensus sequence in each HIV-1 group and HIV-1 group M variant for each 11 CS. Conclusions: This is the first study to describe the CS conservation level across all HIV-1 variants and 11 sites in one of the largest available sequence HIV-1 dataset. These results could help other researchers for the future design of both novel antiretroviral agents acting as maturation inhibitors as well as for vaccine targeting CS. [ABSTRACT FROM AUTHOR]

Discovering all the genetic causes of a phenotype is an important goal in functional genomics. We combine an experimental design for detecting independent genetic causes of a phenotype with a high-throughput sequencing analysis that maximizes sensitivity for comprehensively identifying them. Testing this approach on a set of 24 mutant strains generated for a metabolic phenotype with many known genetic causes, we show that this pathway-based phenotype sequencing analysis greatly improves sensitivity of detection compared with previous methods, and reveals a wide range of pathways that can cause this phenotype. We demonstrate our approach on a metabolic re-engineering phenotype, the PEP/OAA metabolic node in E. coli, which is crucial to a substantial number of metabolic pathways and under renewed interest for biofuel research. Out of 2157 mutations in these strains, pathway-phenoseq discriminated just five gene groups (12 genes) as statistically significant causes of the phenotype. Experimentally, these five gene groups, and the next two high-scoring pathway-phenoseq groups, either have a clear connection to the PEP metabolite level or offer an alternative path of producing oxaloacetate (OAA), and thus clearly explain the phenotype. These high-scoring gene groups also show strong evidence of positive selection pressure, compared with strictly neutral selection in the rest of the genome. [ABSTRACT FROM AUTHOR]

Metagenomic approaches are widespread in microbiological research, but so far, the knowledge on extrachromosomal DNA diversity and composition has largely remained dependant on cultivating host organisms. Even with the emergence of metagenomics, complete circular sequences are rarely identified, and have required manual curation. We propose a robust in silico procedure for identifying complete small plasmids in metagenomic datasets from whole genome shotgun sequencing. From one very pure and exhaustively sequenced metamobilome from rat cecum, we identified a total of 616 circular sequences, 160 of which were carrying a gene with plasmid replication domain. Further homology analyses indicated that the majority of these plasmid sequences are novel. We confirmed the circularity of the complete plasmid candidates using an inverse-type PCR approach on a subset of sequences with 95% success, confirming the existence and length of discrete sequences. The implication of these findings is a broadened understanding of the traits of circular elements in nature and the possibility of massive data mining in existing metagenomic datasets to discover novel pools of complete plasmids thus vastly expanding the current plasmid database. [ABSTRACT FROM AUTHOR]

Genome-wide mapping of transcription factor binding and histone modification reveals complex patterns of interactions. Identifying overlaps in binding patterns by different factors is a major objective of genomic studies, but existing methods to archive large numbers of datasets in a personalised database lack sophistication and utility. Therefore we have developed transcription factor DNA binding site analyser software (BiSA), for archiving of binding regions and easy identification of overlap with or proximity to other regions of interest. Analysis results can be restricted by chromosome or base pair overlap between regions or maximum distance between binding peaks. BiSA is capable of reporting overlapping regions that share common base pairs; regions that are nearby; regions that are not overlapping; and average region sizes. BiSA can identify genes located near binding regions of interest, genomic features near a gene or locus of interest and statistical significance of overlapping regions can also be reported. Overlapping results can be visualized as Venn diagrams. A major strength of BiSA is that it is supported by a comprehensive database of publicly available transcription factor binding sites and histone modifications, which can be directly compared to user data. The documentation and source code are available on http://bisa.sourceforge.net [ABSTRACT FROM AUTHOR]

As the cost of whole genome sequencing (WGS) decreases, clinical laboratories will be looking at broadly adopting this technology to screen for variants of clinical significance. To fully leverage this technology in a clinical setting, results need to be reported quickly, as the turnaround rate could potentially impact patient care. The latest sequencers can sequence a whole human genome in about 24 hours. However, depending on the computing infrastructure available, the processing of data can take several days, with the majority of computing time devoted to aligning reads to genomics regions that are to date not clinically interpretable. In an attempt to accelerate the reporting of clinically actionable variants, we have investigated the utility of a multi-step alignment algorithm focused on aligning reads and calling variants in genomic regions of clinical relevance prior to processing the remaining reads on the whole genome. This iterative workflow significantly accelerates the reporting of clinically actionable variants with no loss of accuracy when compared to genotypes obtained with the OMNI SNP platform or to variants detected with a standard workflow that combines Novoalign and GATK. [ABSTRACT FROM AUTHOR]

Two-component signal transduction systems are commonly composed of a sensor histidine kinase and a cognate response regulator, modulating gene expression in response to environmental changes through a phosphorylation-dependent process. CosR is an OmpR-type response regulator essential for the viability of Campylobacter jejuni, a major foodborne pathogenic species causing human gastroenteritis. Although CosR is a response regulator, its cognate sensor kinase has not been identified in C. jejuni. In this study, DNA sequence analysis of the cosR flanking regions revealed that a gene encoding a putative sensor kinase, which we named cosS, is prevalent in non-thermotolerant Campylobacter spp., but not in thermotolerant campylobacters. Phosphorylation assays indicated that C. fetus CosS rapidly autophosphorylates and then phosphorylates C. fetus CosR, suggesting that the CosRS system constitutes a paired two-component signal transduction system in C. fetus. However, C. fetus CosS does not phosphorylate C. jejuni CosR, suggesting that CosR may have different regulatory cascades between thermotolerant and non-thermotolerant Campylobacter species. Comparison of CosR homolog amino acid sequences showed that the conserved phosphorylation residue (D51), which is present in all non-thermotolerant Campylobacter spp., is absent from the CosR homologs of thermotolerant Campylobacter species. However, C. jejuni CosR was not phosphorylated by C. fetus CosS even after site-directed mutagenesis of N51D, implying that C. jejuni CosR may possibly function phosphorylation-independently. In addition, the results of cosS mutational analysis indicated that CosS is not associated with the temperature dependence of the Campylobacter spp. despite its unique divergent distribution only in non-thermotolerant campylobacters. The findings in this study strongly suggest that thermotolerant and non-thermotolerant Campylobacter spp. have different signal sensing mechanisms associated with the CosR regulation. [ABSTRACT FROM AUTHOR]

Background: We previously identified a novel gene family dispersed in the genome of Schistosoma japonicum by retrotransposon-mediated gene duplication mechanism. Although many transcripts were identified, no homolog was readily identifiable from sequence information. Methodology/Principal Findings: Here, we utilized structural homology modeling and biochemical methods to identify remote homologs, and characterized the gene products as SEA (sea-urchin sperm protein, enterokinase and agrin)-domain containing proteins. A common extracellular domain in this family was structurally similar to SEA-domain. SEA-domain is primarily a structural domain, known to assist or regulate binding to glycans. Recombinant proteins from three members of this gene family specifically interacted with glycosaminoglycans with high affinity, with potential implication in ligand acquisition and immune evasion. Similar approach was used to identify a heme-binding site on the SEA-domain. The heme-binding mode showed heme molecule inserted into a hydrophobic pocket, with heme iron putatively coordinated to two histidine axial ligands. Heme-binding properties were confirmed using biochemical assays and UV-visible absorption spectroscopy, which showed high affinity heme-binding (KD = 1.605×10−6 M) and cognate spectroscopic attributes of hexa-coordinated heme iron. The native proteins were oligomers, antigenic, and are localized on adult worm teguments and gastrodermis; major host-parasite interfaces and site for heme detoxification and acquisition. Conclusions: The results suggest potential role, at least in the nucleation step of heme crystallization (hemozoin formation), and as receptors for heme uptake. Survival strategies exploited by parasites, including heme homeostasis mechanism in hemoparasites, are paramount for successful parasitism. Thus, assessing prospects for application in disease intervention is warranted. [ABSTRACT FROM AUTHOR]

The rearrangement of pre-existing genes has long been thought of as the major mode of new gene generation. Recently, de novo gene birth from non-genic DNA was found to be an alternative mechanism to generate novel protein-coding genes. However, its functional role in human disease remains largely unknown. Here we show that NCYM, a cis-antisense gene of the MYCN oncogene, initially thought to be a large non-coding RNA, encodes a de novo evolved protein regulating the pathogenesis of human cancers, particularly neuroblastoma. The NCYM gene is evolutionally conserved only in the taxonomic group containing humans and chimpanzees. In primary human neuroblastomas, NCYM is 100% co-amplified and co-expressed with MYCN, and NCYM mRNA expression is associated with poor clinical outcome. MYCN directly transactivates both NCYM and MYCN mRNA, whereas NCYM stabilizes MYCN protein by inhibiting the activity of GSK3β, a kinase that promotes MYCN degradation. In contrast to MYCN transgenic mice, neuroblastomas in MYCN/NCYM double transgenic mice were frequently accompanied by distant metastases, behavior reminiscent of human neuroblastomas with MYCN amplification. The NCYM protein also interacts with GSK3β, thereby stabilizing the MYCN protein in the tumors of the MYCN/NCYM double transgenic mice. Thus, these results suggest that GSK3β inhibition by NCYM stabilizes the MYCN protein both in vitro and in vivo. Furthermore, the survival of MYCN transgenic mice bearing neuroblastoma was improved by treatment with NVP-BEZ235, a dual PI3K/mTOR inhibitor shown to destabilize MYCN via GSK3β activation. In contrast, tumors caused in MYCN/NCYM double transgenic mice showed chemo-resistance to the drug. Collectively, our results show that NCYM is the first de novo evolved protein known to act as an oncopromoting factor in human cancer, and suggest that de novo evolved proteins may functionally characterize human disease. [ABSTRACT FROM AUTHOR]

Citrus is one of the most important and widely grown fruit crop with global production ranking firstly among all the fruit crops in the world. Sweet orange accounts for more than half of the Citrus production both in fresh fruit and processed juice. We have sequenced the draft genome of a double-haploid sweet orange (C. sinensis cv. Valencia), and constructed the Citrus sinensis annotation project (CAP) to store and visualize the sequenced genomic and transcriptome data. CAP provides GBrowse-based organization of sweet orange genomic data, which integrates ab initio gene prediction, EST, RNA-seq and RNA-paired end tag (RNA-PET) evidence-based gene annotation. Furthermore, we provide a user-friendly web interface to show the predicted protein-protein interactions (PPIs) and metabolic pathways in sweet orange. CAP provides comprehensive information beneficial to the researchers of sweet orange and other woody plants, which is freely available at http://citrus.hzau.edu.cn/. [ABSTRACT FROM AUTHOR]

Background: Insulin receptor substrate-2 (IRS-2), a signaling adaptor protein, was involved in two cancer-related pathways (the phosphatidylinositol 3′-kinase (PI3K) and the extracellular signal-regulated kinase (ERK) pathways). Several studies have evaluated the association between IRS2 rs1805097 (G>A) polymorphisms and the risk of colorectal and breast cancer. However, the results were inconsistent. Methodology/Principal Findings: A meta-analysis of seven published case-control studies (4 studies with 4798 cases and 5478 controls for colorectal cancer and 3 studies with 2108 cases and 2507 controls for breast cancer) were conducted to assess the strength of association using crude odd ratios (ORs) with 95% confidence intervals (CIs). For colorectal cancer, no obvious associations were found for all genetic models (homozygote comparison OR = 0.96, 95%CI 0.85–1.08, Pheterogeneity = 0.97; heterozygote comparison: OR = 0.91, 95%CI 0.73–1.13, Pheterogeneity<0.01; dominant model: OR = 0.92, 95%CI 0.80–1.06, Pheterogeneity = 0.05; recessive model: OR = 1.02, 95%CI 0.91–1.14, Pheterogeneity = 0.60). In the subgroup analysis by ethnicity, control source and consistency of frequency with Hardy-Weinberg equilibrium (HWE), still no significant associations were observed. For breast cancer, also no obvious associations were found for all genetic models (homozygote comparison: OR = 0.95, 95%CI 0.71–1.26, Pheterogeneity = 0.10; heterozygote comparison: OR = 1.00, 95%CI 0.89–1.14, Pheterogeneity = 0.71; dominant model: OR = 0.98, 95%CI 0.87–1.10, Pheterogeneity = 0.55; recessive model: OR = 0.95, 95%CI 0.72–1.25, Pheterogeneity = 0.07). We performed subgroup analyses by sample size and did not find an association. Conclusions: This meta-analysis indicated that IRS2 rs1805097polymorphism was not associated with colorectal and breast cancer risk. [ABSTRACT FROM AUTHOR]

Periodontitis is a progressive disease of the periodontium with a complex, polymicrobial etiology. Recent Next-Generation Sequencing (NGS) studies of the microbial diversity associated with periodontitis have revealed strong, community-level differences in bacterial assemblages associated with healthy or diseased periodontal sites. In this study, we used NGS approaches to characterize changes in periodontal pocket bacterial diversity after standard periodontal treatment. Despite consistent changes in the abundance of certain taxa in individuals whose condition improved with treatment, post-treatment samples retained the highest similarity to pre-treatment samples from the same individual. Deeper phylogenetic analysis of periodontal pathogen-containing genera Prevotella and Fusobacterium found both unexpected diversity and differential treatment response among species. Our results highlight how understanding interpersonal variability among microbiomes is necessary for determining how polymicrobial diseases respond to treatment and disturbance. [ABSTRACT FROM AUTHOR]

The Human Oral Microbiome Database (HOMD) provides an extensive collection of genome sequences from oral bacteria. The sequence information is a static snapshot of the microbial potential of the so far sequenced species. A major challenge is to connect the microbial potential encoded in the metagenome to an actual function in the in vivo oral biofilm. In the present study we took a reductionist approach and identified a considerably conserved metabolic gene, spxB to be encoded by a majority of oral streptococci using the HOMD metagenome information. spxB encodes the pyruvate oxidase responsible for the production of growth inhibiting amounts of hydrogen peroxide (H2O2) and has previously been shown as important in the interspecies competition in the oral biofilm. Here we demonstrate a strong correlation of H2O2 production and the presence of the spxB gene in dental plaque. Using Real-Time RT PCR we show that spxB is expressed in freshly isolated human plaque samples from several donors and that the expression is relative constant when followed over time in one individual. This is the first demonstration of an oral community encoded gene expressed in vivo suggesting a functional role of spxB in oral biofilm physiology. This also demonstrates a possible strategy to connect the microbial potential of the metagenome to its functionality in future studies by identifying similar highly conserved genes in the oral microbial community. [ABSTRACT FROM AUTHOR]

The Bacillus phage phiAGATE is a novel myovirus isolated from the waters of Lake Góreckie (a eutrophic lake in western Poland). The bacteriophage infects Bacillus pumilus, a bacterium commonly observed in the mentioned reservoir. Analysis of the phiAGATE genome (149844 base pairs) resulted in 204 predicted protein-coding sequences (CDSs), of which 53 could be functionally annotated. Further investigation revealed that the bacteriophage is a member of a previously undescribed cluster of phages (for the purposes of this study we refer to it as “Bastille group”) within the Spounavirinae subfamily. Here we demonstrate that these viruses constitute a distinct branch of the Spounavirinae phylogenetic tree, with limited similarity to phages from the Twortlikevirus and Spounalikevirus genera. The classification of phages from the Bastille group into any currently accepted genus proved extremely difficult, prompting concerns about the validity of the present taxonomic arrangement of the subfamily. [ABSTRACT FROM AUTHOR]

Background: Genetic and genomic data analyses are outputting large sets of genes. Functional comparison of these gene sets is a key part of the analysis, as it identifies their shared functions, and the functions that distinguish each set. The Gene Ontology (GO) initiative provides a unified reference for analyzing the genes molecular functions, biological processes and cellular components. Numerous semantic similarity measures have been developed to systematically quantify the weight of the GO terms shared by two genes. We studied how gene set comparisons can be improved by considering gene set particularity in addition to gene set similarity. Results: We propose a new approach to compute gene set particularities based on the information conveyed by GO terms. A GO term informativeness can be computed using either its information content based on the term frequency in a corpus, or a function of the term's distance to the root. We defined the semantic particularity of a set of GO terms Sg1 compared to another set of GO terms Sg2. We combined our particularity measure with a similarity measure to compare gene sets. We demonstrated that the combination of semantic similarity and semantic particularity measures was able to identify genes with particular functions from among similar genes. This differentiation was not recognized using only a semantic similarity measure. Conclusion: Semantic particularity should be used in conjunction with semantic similarity to perform functional analysis of GO-annotated gene sets. The principle is generalizable to other ontologies. [ABSTRACT FROM AUTHOR]