HGCA2.0: An RNA-Seq Based Webtool for Gene Coexpression Analysis in Homo sapiens

Genes with similar expression patterns in a set of diverse samples may be considered coexpressed. Human Gene Coexpression Analysis 2.0 (HGCA2.0) is a webtool which studies the global coexpression landscape of human genes. The website is based on the hierarchical clustering of 55,431 Homo sapiens genes based on a large-scale coexpression analysis of 3500 GTEx bulk RNA-Seq samples of healthy individuals, which were selected as the best representative samples of each tissue type. HGCA2.0 presents subclades of coexpressed genes to a gene of interest, and performs various built-in gene term enrichment analyses on the coexpressed genes, including gene ontologies, biological pathways, protein families, and diseases, while also being unique in revealing enriched transcription factors driving coexpression. HGCA2.0 has been successful in identifying not only genes with ubiquitous expression patterns, but also tissue-specific genes. Benchmarking showed that HGCA2.0 belongs to the top performing coexpression webtools, as shown by STRING analysis. HGCA2.0 creates working hypotheses for the discovery of gene partners or common biological processes that can be experimentally validated. It offers a simple and intuitive website design and user interface, as well as an API endpoint.

The correlation of substitution effects across populations and generations in the presence of nonadditive functional gene action

Allele substitution effects at quantitative trait loci (QTL) are part of the basis of quantitative genetics theory and applications such as association analysis and genomic prediction. In the presence of nonadditive functional gene action, substitution effects are not constant across populations. We develop an original approach to model the difference in substitution effects across populations as a first order Taylor series expansion from a "focal" population. This expansion involves the difference in allele frequencies and second-order statistical effects (additive by additive and dominance). The change in allele frequencies is a function of relationships (or genetic distances) across populations. As a result, it is possible to estimate the correlation of substitution effects across two populations using three elements: magnitudes of additive, dominance, and additive by additive variances; relationships (Nei's minimum distances or Fst indexes); and assumed heterozygosities. Similarly, the theory applies as well to distinct generations in a population, in which case the distance across generations is a function of increase of inbreeding. Simulation results confirmed our derivations. Slight biases were observed, depending on the nonadditive mechanism and the reference allele. Our derivations are useful to understand and forecast the possibility of prediction across populations and the similarity of GWAS effects.

Comparative transcriptomic analysis for identification of candidate sex-related genes and pathways in Crimson seabream (Parargyrops edita)

Teleost fishes display the largest array of sex-determining systems among animals, resulting in various reproductive strategies. Research on sex-related genes in teleosts will broaden our understanding of the process, and provide important insight into the plasticity of the sex determination process in vertebrates in general. Crimson seabream (Parargyrops edita Tanaka, 1916) is one of the most valuable and abundant fish resources throughout Asia. However, little genomic information on P. edita is available. In the present study, the transcriptomes of male and female P. edita were sequenced with RNA-seq technology. A total of 388,683,472 reads were generated from the libraries. After filtering and assembling, a total of 79,775 non redundant unigenes were obtained with an N50 of 2,921 bp. The unigenes were annotated with multiple public databases, including NT (53,556, 67.13%), NR (54,092, 67.81%), Swiss-Prot (45,265, 56.74%), KOG (41,274, 51.74%), KEGG (46,302, 58.04%), and GO (11,056, 13.86%) databases. Comparison of the unigenes of different sexes of P. edita revealed that 11,676 unigenes (9,335 in females, 2,341 in males) were differentially expressed between males and females. Of these, 5,463 were specifically expressed in females, and 1,134 were specifically expressed in males. In addition, the expression levels of ten unigenes were confirmed to validate the transcriptomic data by qRT-PCR. Moreover, 34,473 simple sequence repeats (SSRs) were identified in SSR-containing sequences, and 50 loci were randomly selected for primer development. Of these, 36 loci were successfully amplified, and 19 loci were polymorphic. Finally, our comparative analysis identified many sex-related genes (zps, amh, gsdf, sox4, cyp19a, etc.) and pathways (MAPK signaling pathway, p53 signaling pathway, etc.) of P. edita. This informative transcriptomic analysis provides valuable data to increase genomic resources of P. edita. The results will be useful for clarifying the molecular mechanism of sex determination and for future functional analyses of sex-associated genes.

Exploring the genetic basis of fatty liver development in geese

Although geese possess an adaptive physiological capacity for lipid storage, few candidate genes contributing to this ability are characterised. By comparing the genomes of individuals with extremely high and low fatty liver weights (FLW), candidate genes were identified, including ARAP2, GABRE, and IL6. Single-nucleotide polymorphisms in or near these genes were significantly (p < 0.05) associated with carcass traits (FLW) and biochemical indexes (very-low-density lipoprotein and N-terminal procollagen III), suggesting contribution to trait variation. A common variant at the 5'-end of LCORL explained ~ 18% and ~ 26% of the phenotypic variance in body weight with/without overfeeding and had significant effects on FLW (p < 0.01). ZFF36L1, ARHGEF1 and IQCJ, involved in bile acid metabolism, blood pressure, and lipid concentration modulation, were also identified. The presence of highly divergent haplotypes within these genes suggested involvement in protection against negative effects from excessive lipids in the liver or circulatory system. Based on this and transcriptomic data, we concluded that geese hepatosteatosis results from severe imbalance between lipid accumulation and secretion, comparable to human non-alcohol fatty liver disease but involving other genes. Our results provided valuable insights into the genesis of geese fatty liver and detected potential target genes for treatment of lipid-related diseases.

Identification of key genes in calcific aortic valve disease by integrated bioinformatics analysis

Calcific aortic valve disease (CAVD) is highly prevalent in our aging world and has no effective pharmaceutical treatment. Intense efforts have been made but the underlying molecular mechanisms of CAVD are still unclear.This study was designed to identify the critical genes and pathways in CAVD by bioinformatics analysis. Microarray datasets of GSE12644, GSE51472, and GSE83453 were obtained from Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified and functional and pathway enrichment analysis was performed. Subsequently, the protein-protein interaction network (PPI) was constructed with Search Tool for the Retrieval of Interacting Genes and was visualized with Cytoscape to identify the most significant module. Hub genes were identified by Cytoscape plugin cytoHubba.A total of 179 DEGs, including 101 upregulated genes and 78 downregulated genes, were identified. The enriched functions and pathways of the DEGs include inflammatory and immune response, chemotaxis, extracellular matrix (ECM) organization, complement and coagulation cascades, ECM receptor interaction, and focal adhesion. The most significant module in the PPI network was analyzed and genes among it were mainly enriched in chemotaxis, locomotory behavior, immune response, chemokine signaling pathway, and extracellular space. In addition, DEGs, with degrees ≥ 10 and the top 10 highest Maximal Chique Centrality (MCC) score, were identified as hub genes. CCR1, MMP9, VCAM1, and ITGAX, which were of the highest degree or MCC score, were manually reviewed.The DEGs and hub genes identified in the present study help us understand the molecular mechanisms underlying the pathogenesis of CAVD and might serve as candidate therapeutic targets for CAVD.

Rapid sex-specific adaptation to high temperature in Drosophila

The pervasive occurrence of sexual dimorphism demonstrates different adaptive strategies of males and females. While different reproductive strategies of the two sexes are well-characterized, very little is known about differential functional requirements of males and females in their natural habitats. Here, we study the impact environmental change on the selection response in both sexes. Exposing replicated Drosophila populations to a novel temperature regime, we demonstrate sex-specific changes in gene expression, metabolic and behavioral phenotypes in less than 100 generations. This indicates not only different functional requirements of both sexes in the new environment but also rapid sex-specific adaptation. Supported by computer simulations we propose that altered sex-biased gene regulation from standing genetic variation, rather than new mutations, is the driver of rapid sex-specific adaptation. Our discovery of environmentally driven divergent functional requirements of males and females has important implications-possibly even for gender aware medical treatments.

A new biological definition of life

Here we have proposed a new biological definition of life based on the function and reproduction of existing genes and creation of new ones, which is applicable to both unicellular and multicellular organisms. First, we coined a new term "genetic information metabolism" comprising functioning, reproduction, and creation of genes and their distribution among living and non-living carriers of genetic information. Encompassing this concept, life is defined as organized matter that provides genetic information metabolism. Additionally, we have articulated the general biological function of life as Tetz biological law: "General biological function of life is to provide genetic information metabolism" and formulated novel definition of life: "Life is an organized matter that provides genetic information metabolism". New definition of life and Tetz biological law allow to distinguish in a new way living and non-living objects on Earth and other planets based on providing genetic information metabolism.

NMFGO: Gene Function Prediction via Nonnegative Matrix Factorization with Gene Ontology

Gene Ontology (GO) is a controlled vocabulary of terms that describe molecule function, biological roles, and cellular locations of gene products (i.e., proteins and RNAs), it hierarchically organizes more than 43,000 GO terms via the direct acyclic graph. A gene is generally annotated with several of these GO terms. Therefore, accurately predicting the association between genes and massive terms is a difficult challenge. To combat with this challenge, we propose an matrix factorization based approach called NMFGO. NMFGO stores the available GO annotations of genes in a gene-term association matrix and adopts an ontological structure based taxonomic similarity measure to capture the GO hierarchy. Next, it factorizes the association matrix into two low-rank matrices via nonnegative matrix factorization regularized with the GO hierarchy. After that, it employs a semantic similarity based k nearest neighbor classifier in the low-rank matrices approximated subspace to predict gene functions. Empirical study on three model species (S. cerevisiae, H. sapiens, and A. thaliana) shows that NMFGO is robust to the input parameters and achieves significantly better prediction performance than GIC, TO, dRW- kNN, and NtN, which were re-implemented based on the instructions of the original papers. The supplementary file and demo codes of NMFGO are available at http://mlda.swu.edu.cn/codes.php?name=NMFGO.

Bioinformatic analysis of the molecular mechanism underlying bronchial pulmonary dysplasia using a text mining approach

Bronchopulmonary dysplasia (BPD) is a common disease of premature infants with very low birth weight. The mechanism is inconclusive. The aim of this study is to systematically explore BPD-related genes and characterize their functions.Natural language processing analysis was used to identify BPD-related genes. Gene data were extracted from PubMed database. Gene ontology, pathway, and network analysis were carried out, and the result was integrated with corresponding database.In this study, 216 genes were identified as BPD-related genes with P < .05, and 30 pathways were identified as significant. A network of BPD-related genes was also constructed with 17 hub genes identified. In particular, phosphatidyl inositol-3-enzyme-serine/threonine kinase signaling pathway involved the largest number of genes. Insulin was found to be a promising candidate gene related with BPD, suggesting that it may serve as an effective therapeutic target.Our data may help to better understand the molecular mechanisms underlying BPD. However, the mechanisms of BPD are elusive, and further studies are needed.

New alcohol-related genes suggest shared genetic mechanisms with neuropsychiatric disorders

Excessive alcohol consumption is one of the main causes of death and disability worldwide. Alcohol consumption is a heritable complex trait. Here we conducted a meta-analysis of genome-wide association studies of alcohol consumption (g d-1) from the UK Biobank, the Alcohol Genome-Wide Consortium and the Cohorts for Heart and Aging Research in Genomic Epidemiology Plus consortia, collecting data from 480,842 people of European descent to decipher the genetic architecture of alcohol intake. We identified 46 new common loci and investigated their potential functional importance using magnetic resonance imaging data and gene expression studies. We identify genetic pathways associated with alcohol consumption and suggest genetic mechanisms that are shared with neuropsychiatric disorders such as schizophrenia.

Genes that make you fat, but keep you healthy

Obesity prevalence continues to rise worldwide, posing a substantial burden on people's health. However, up to 45% of obese individuals do not suffer from cardiometabolic complications, also called the metabolically healthy obese (MHO). Concurrently, up to 30% of normal-weight individuals demonstrate cardiometabolic risk factors that are generally observed in obese individuals, the metabolically obese normal weight (MONW). Besides lifestyle, environmental factors and demographic factors, innate biological mechanisms are known to contribute to the aetiology of the MHO and MONW phenotypes, as well. Experimental studies in animal models have shown that adipose tissue expandability, fat distribution, adipogenesis, adipose tissue vascularization, inflammation and fibrosis, and mitochondrial function are the main mechanisms that uncouple adiposity from its cardiometabolic comorbidities. We reviewed current genetic association studies to expand insights into the biology of MHO/MONW phenotypes. At least four genetic loci were identified through genome-wide association studies for body fat percentage (BF%) of which the BF%-increasing allele was associated with a protective effect on glycemic and lipid outcomes. For some, this association was mediated through favourable effects on body fat distribution. Other studies that characterized the genetic susceptibility of insulin resistance found that a higher susceptibility was associated with lower overall adiposity due to less fat accumulation at hips and legs, suggesting that an impaired capacity to store fat subcutaneously or a preferential storage in the intra-abdominal cavity may be metabolically harmful. Clearly, more work remains to be done in this field, first through gene discovery and subsequently through functional follow-up of identified genes.

Long negative feedback loop enhances period tunability of biological oscillators

Oscillatory phenomena play a major role in organisms. In some biological oscillations such as cell cycles and heartbeats, the period can be tuned without significant changes in the amplitude. This property is called (period) tunability, one of the prominent features of biological oscillations. However, how biological oscillators produce tunable oscillations remains largely unexplored. We tackle this question using computational experiments. It has been reported that positive-plus-negative feedback oscillators produce tunable oscillations through the hysteresis-based mechanism. First, in this study, we confirmed that positive-plus-negative feedback oscillators generate tunable oscillations. Second, we found that tunability is positively correlated with the dynamic range of oscillations. Third, we showed that long negative feedback oscillators without any additional positive feedback loops can produce tunable oscillations. Finally, we computationally demonstrated that by lengthening the negative feedback loop, the Repressilator, known as a non-tunable synthetic gene oscillator, can be converted into a tunable oscillator. This work provides synthetic biologists with clues to design tunable gene oscillators.

Inferring Unknown Biological Function by Integration of GO Annotations and Gene Expression Data

Characterizing genes with semantic information is an important process regarding the description of gene products. In spite that complete genomes of many organisms have been already sequenced, the biological functions of all of their genes are still unknown. Since experimentally studying the functions of those genes, one by one, would be unfeasible, new computational methods for gene functions inference are needed. We present here a novel computational approach for inferring biological function for a set of genes with previously unknown function, given a set of genes with well-known information. This approach is based on the premise that genes with similar behaviour should be grouped together. This is known as the guilt-by-association principle. Thus, it is possible to take advantage of clustering techniques to obtain groups of unknown genes that are co-clustered with genes that have well-known semantic information (GO annotations). Meaningful knowledge to infer unknown semantic information can therefore be provided by these well-known genes. We provide a method to explore the potential function of new genes according to those currently annotated. The results obtained indicate that the proposed approach could be a useful and effective tool when used by biologists to guide the inference of biological functions for recently discovered genes. Our work sets an important landmark in the field of identifying unknown gene functions through clustering, using an external source of biological input. A simple web interface to this proposal can be found at http://fich.unl.edu.ar/sinc/webdemo/gamma-am/.

Transcriptomic profiling in muscle and adipose tissue identifies genes related to growth and lipid deposition

Growth performance and meat quality are important traits for the pig industry and consumers. Adipose tissue is the main site at which fat storage and fatty acid synthesis occur. Therefore, we combined high-throughput transcriptomic sequencing in adipose and muscle tissues with the quantification of corresponding phenotypic features using seven Chinese indigenous pig breeds and one Western commercial breed (Yorkshire). We obtained data on 101 phenotypic traits, from which principal component analysis distinguished two groups: one associated with the Chinese breeds and one with Yorkshire. The numbers of differentially expressed genes between all Chinese breeds and Yorkshire were shown to be 673 and 1056 in adipose and muscle tissues, respectively. Functional enrichment analysis revealed that these genes are associated with biological functions and canonical pathways related to oxidoreductase activity, immune response, and metabolic process. Weighted gene coexpression network analysis found more coexpression modules significantly correlated with the measured phenotypic traits in adipose than in muscle, indicating that adipose regulates meat and carcass quality. Using the combination of differential expression, QTL information, gene significance, and module hub genes, we identified a large number of candidate genes potentially related to economically important traits in pig, which should help us improve meat production and quality.

Expression of uncharacterized male germ cell-specific genes and discovery of novel sperm-tail proteins in mice

The identification and characterization of germ cell-specific genes are essential if we hope to comprehensively understand the mechanisms of spermatogenesis and fertilization. Here, we searched the mouse UniGene databases and identified 13 novel genes as being putatively testis-specific or -predominant. Our in silico and in vitro analyses revealed that the expressions of these genes are testis- and germ cell-specific, and that they are regulated in a stage-specific manner during spermatogenesis. We generated antibodies against the proteins encoded by seven of the genes to facilitate their characterization in male germ cells. Immunoblotting and immunofluorescence analyses revealed that one of these proteins was expressed only in testicular germ cells, three were expressed in both testicular germ cells and testicular sperm, and the remaining three were expressed in sperm of the testicular stages and in mature sperm from the epididymis. Further analysis of the latter three proteins showed that they were all associated with cytoskeletal structures in the sperm flagellum. Among them, MORN5, which is predicted to contain three MORN motifs, is conserved between mouse and human sperm. In conclusion, we herein identify 13 authentic genes with male germ cell-specific expression, and provide comprehensive information about these genes and their encoded products. Our finding will facilitate future investigations into the functional roles of these novel genes in spermatogenesis and sperm functions.

Robustness of synthetic oscillators in growing and dividing cells

Synthetic biology sets out to implement new functions in cells, and to develop a deeper understanding of biological design principles. Elowitz and Leibler [Nature (London) 403, 335 (2000)NATUAS0028-083610.1038/35002125] showed that by rational design of the reaction network, and using existing biological components, they could create a network that exhibits periodic gene expression, dubbed the repressilator. More recently, Stricker et al. [Nature (London) 456, 516 (2008)NATUAS0028-083610.1038/nature07389] presented another synthetic oscillator, called the dual-feedback oscillator, which is more stable. Detailed studies have been carried out to determine how the stability of these oscillators is affected by the intrinsic noise of the interactions between the components and the stochastic expression of their genes. However, as all biological oscillators reside in growing and dividing cells, an important question is how these oscillators are perturbed by the cell cycle. In previous work we showed that the periodic doubling of the gene copy numbers due to DNA replication can couple not only natural, circadian oscillators to the cell cycle [Paijmans et al., Proc. Natl. Acad. Sci. (USA) 113, 4063 (2016)PNASA60027-842410.1073/pnas.1507291113], but also these synthetic oscillators. Here we expand this study. We find that the strength of the locking between oscillators depends not only on the positions of the genes on the chromosome, but also on the noise in the timing of gene replication: noise tends to weaken the coupling. Yet, even in the limit of high levels of noise in the replication times of the genes, both synthetic oscillators show clear signatures of locking to the cell cycle. This work enhances our understanding of the design of robust biological oscillators inside growing and diving cells.

Genes, body clocks and prevention of sleep problems

Chronobiologists argue that their scientific findings have implications for prevention of sleep problems. They claim that some sleep problems are caused by the fact that people live against their individual body clock rather than adjusted to it. They also claim that by taking the findings of chronobiology seriously in policy-making some sleep problems can be prevented. I investigate applications of chronobiology in two social areas-school schedules and shift work-and show that in order for these applications to be justified certain implicit presumptions have to be justified. The first presumption is explanatory, namely that a chronobiological explanation is an adequate explanation of the sleep problems at hand. In addition I analyse three ethical presumptions. The first ethical presumption is that sleep is of vital value. The second is that sleep is not an exclusively private issue. The third ethical presumption is that the preventive measures to be undertaken are ethically acceptable. My main point is that it is not possible to simply "read off" policy measures from the empirical findings of chronobiology.

Predicting gene functions from multiple biological sources using novel ensemble methods

The functional classification of genes plays a vital role in molecular biology. Detecting previously unknown role of genes and their products in physiological and pathological processes is an important and challenging problem. In this work, information from several biological sources such as comparative genome sequences, gene expression and protein interactions are combined to obtain robust results on predicting gene functions. The information in such heterogeneous sources is often incomplete and hence making the maximum use of all the available information is a challenging problem. We propose an algorithm that improves the performance of prediction of different models built on individual sources. We also develop a heterogeneous boosting framework that uses all the available information even if some sources do not provide any information about some of the genes. We demonstrate the superior performance of the proposed methods in terms of accuracy and F-measure compared to several imputation and integration schemes.

The Search for the Genetic Basis of Aging: The Identification of Gerontogenes in the NematodeCaenorhabditis elegans

Study of C. elegans has provided much information for gerontologists. The influence of the genome on life span is clearly observable, and at least one gerontogene, age-1, has been defined. Data relating to important evolutionary questions has emerged and will continue to be used in testing current hypotheses. We are using an approach unbiased by theoretical constraints to delineate aging processes simultaneously at the molecular and organismal levels. Much remains to be discovered before fundamental questions posed in this article are answered to a satisfactory degree. The immediate agenda is the identification and isolation of gerontogenes which influence life span in invertebrate models. This work is well in hand and will lead to the unraveling of specific life-span-determining processes. At this point we may be able to predict whether analogous processes also limit life in mammals. If we are fortunate and aging processes exhibit evolutionary conservation, many exciting possibilities await. Molecular tools provided by the invertebrate system can then be used to isolate homologous mammalian gerontogenes that could be subsequently utilized in highly targeted attempts to intervene in mammalian aging. This offers the most direct strategy for identifying life-span prolongation genes in humans.

EJE Prize 2012: Obesity: from genes to behaviour

An increase in the consumption of highly palatable foods coupled with a reduction in the amount of voluntary exercise undertaken has contributed to the rising prevalence of obesity. However, despite the obvious environmental influences, there is considerable evidence to support a genetic component to weight gain. In some people, particularly those who are severely obese, genetic factors play a major role in the development of their obesity and associated complications. Studies into the genetic basis of obesity have yielded insights into the mechanisms involved in the regulation of weight. We now understand that weight is regulated by neural mechanisms that regulate appetite and energy expenditure and that disruption of these pathways can result in severe obesity in some patients. These studies provide a starting point for investigating patients with severe obesity and may ultimately guide the development of more rational targeted therapies.

Gene function prediction based on the Gene Ontology hierarchical structure

The information of the Gene Ontology annotation is helpful in the explanation of life science phenomena, and can provide great support for the research of the biomedical field. The use of the Gene Ontology is gradually affecting the way people store and understand bioinformatic data. To facilitate the prediction of gene functions with the aid of text mining methods and existing resources, we transform it into a multi-label top-down classification problem and develop a method that uses the hierarchical relationships in the Gene Ontology structure to relieve the quantitative imbalance of positive and negative training samples. Meanwhile the method enhances the discriminating ability of classifiers by retaining and highlighting the key training samples. Additionally, the top-down classifier based on a tree structure takes the relationship of target classes into consideration and thus solves the incompatibility between the classification results and the Gene Ontology structure. Our experiment on the Gene Ontology annotation corpus achieves an F-value performance of 50.7% (precision: 52.7% recall: 48.9%). The experimental results demonstrate that when the size of training set is small, it can be expanded via topological propagation of associated documents between the parent and child nodes in the tree structure. The top-down classification model applies to the set of texts in an ontology structure or with a hierarchical relationship.

Genetic interaction analysis of point mutations enables interrogation of gene function at a residue-level resolution: exploring the applications of high-resolution genetic interaction mapping of point mutations

We have achieved a residue-level resolution of genetic interaction mapping - a technique that measures how the function of one gene is affected by the alteration of a second gene - by analyzing point mutations. Here, we describe how to interpret point mutant genetic interactions, and outline key applications for the approach, including interrogation of protein interaction interfaces and active sites, and examination of post-translational modifications. Genetic interaction analysis has proven effective for characterizing cellular processes; however, to date, systematic high-throughput genetic interaction screens have relied on gene deletions or knockdowns, which limits the resolution of gene function analysis and poses problems for multifunctional genes. Our point mutant approach addresses these issues, and further provides a tool for in vivo structure-function analysis that complements traditional biophysical methods. We also discuss the potential for genetic interaction mapping of point mutations in human cells and its application to personalized medicine.

Intracortical bone remodeling variation shows strong genetic effects

Intracortical microstructure influences crack propagation and arrest within bone cortex. Genetic variation in intracortical remodeling may contribute to mechanical integrity and, therefore, fracture risk. Our aim was to determine the degree to which normal population-level variation in intracortical microstructure is due to genetic variation. We examined right femurs from 101 baboons (74 females, 27 males; aged 7-33 years) from a single, extended pedigree to determine osteon number, osteon area (On.Ar), haversian canal area, osteon population density, percent osteonal bone (%On.B), wall thickness (W.Th), and cortical porosity (Ct.Po). Through evaluation of the covariance in intracortical properties between pairs of relatives, we quantified the contribution of additive genetic effects (heritability [h (2)]) to variation in these traits using a variance decomposition approach. Significant age and sex effects account for 9 % (Ct.Po) to 21 % (W.Th) of intracortical microstructural variation. After accounting for age and sex, significant genetic effects are evident for On.Ar (h (2) = 0.79, p = 0.002), %On.B (h (2) = 0.82, p = 0.003), and W.Th (h (2) = 0.61, p = 0.013), indicating that 61-82 % of the residual variation (after accounting for age and sex effects) is due to additive genetic effects. This corresponds to 48-75 % of the total phenotypic variance. Our results demonstrate that normal, population-level variation in cortical microstructure is significantly influenced by genes. As a critical mediator of crack behavior in bone cortex, intracortical microstructural variation provides another mechanism through which genetic variation may affect fracture risk.

Inference of gene-phenotype associations via protein-protein interaction and orthology

One of the fundamental goals of genetics is to understand gene functions and their associated phenotypes. To achieve this goal, in this study we developed a computational algorithm that uses orthology and protein-protein interaction information to infer gene-phenotype associations for multiple species. Furthermore, we developed a web server that provides genome-wide phenotype inference for six species: fly, human, mouse, worm, yeast, and zebrafish. We evaluated our inference method by comparing the inferred results with known gene-phenotype associations. The high Area Under the Curve values suggest a significant performance of our method. By applying our method to two human representative diseases, Type 2 Diabetes and Breast Cancer, we demonstrated that our method is able to identify related Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways. The web server can be used to infer functions and putative phenotypes of a gene along with the candidate genes of a phenotype, and thus aids in disease candidate gene discovery. Our web server is available at http://jjwanglab.org/PhenoPPIOrth.

Metagenomic guilt by association: an operonic perspective

Next-generation sequencing projects continue to drive a vast accumulation of metagenomic sequence data. Given the growth rate of this data, automated approaches to functional annotation are indispensable and a cornerstone heuristic of many computational protocols is the concept of guilt by association. The guilt by association paradigm has been heavily exploited by genomic context methods that offer functional predictions that are complementary to homology-based annotations, thereby offering a means to extend functional annotation. In particular, operon methods that exploit co-directional intergenic distances can provide homology-free functional annotation through the transfer of functions among co-operonic genes, under the assumption that guilt by association is indeed applicable. Although guilt by association is a well-accepted annotative device, its applicability to metagenomic functional annotation has not been definitively demonstrated. Here a large-scale assessment of metagenomic guilt by association is undertaken where functional associations are predicted on the basis of co-directional intergenic distances. Specifically, functional annotations are compared within pairs of adjacent co-directional genes, as well as operons of various lengths (i.e. number of member genes), in order to reveal new information about annotative cohesion versus operon length. The results suggests that co-directional gene pairs offer reduced confidence for metagenomic guilt by association due to difficulty in resolving the existence of functional associations when intergenic distance is the sole predictor of pairwise gene interactions. However, metagenomic operons, particularly those with substantial lengths, appear to be capable of providing a superior basis for metagenomic guilt by association due to increased annotative stability. The need for improved recognition of metagenomic operons is discussed, as well as the limitations of the present work.

How environment and genes shape the adolescent brain

This article is part of a Special Issue "Puberty and Adolescence". This review provides a conceptual framework for the study of factors--in our genes and environment--that shape the adolescent brain. I start by pointing out that brain phenotypes obtained with magnetic resonance imaging are complex traits reflecting the interplay of genes and the environment. In some cases, variations in the structural phenotypes observed during adolescence have their origin in the pre-natal or early post-natal periods. I then emphasize the bidirectional nature of brain-behavior relationships observed during this period of human development, where function may be more likely to influence structure rather than vice versa. In the main part of this article, I review our ongoing work on the influence of gonadal hormones on the adolescent brain. I also discuss the importance of social context and brain plasticity on shaping the relevant neural circuits.

Gelsius: a literature-based workflow for determining quantitative associations between genes and biological processes

An effective knowledge extraction and quantification methodology from biomedical literature would allow the researcher to organize and analyze the results of high-throughput experiments on microarrays and next-generation sequencing technologies. Despite the large amount of raw information available on the web, a tool able to extract a measure of the correlation between a list of genes and biological processes is not yet available. In this paper, we present Gelsius, a workflow that incorporates biomedical literature to quantify the correlation between genes and terms describing biological processes. To achieve this target, we build different modules focusing on query expansion and document cononicalization. In this way, we reached to improve the measurement of correlation, performed using a latent semantic analysis approach. To the best of our knowledge, this is the first complete tool able to extract a measure of genes-biological processes correlation from literature. We demonstrate the effectiveness of the proposed workflow on six biological processes and a set of genes, by showing that correlation results for known relationships are in accordance with definitions of gene functions provided by NCI Thesaurus. On the other side, the tool is able to propose new candidate relationships for later experimental validation. The tool is available at >http://bioeda1.polito.it:8080/medSearchServlet/.

Defining genes using "blueprint" versus "instruction" metaphors: effects for genetic determinism, response efficacy, and perceived control

Evidence supports mixed attributions aligned with personal and/or clinical control and gene expression for health in this era of genomic science and health care. We consider variance in these attributions and possible relationships to individual mind sets associated with essentialist beliefs that genes determine health versus threat beliefs that genes increase susceptibility for disease and severity linked to gene-environment interactions. Further, we contribute to theory and empirical research to evaluate the use of metaphors to define genes. Participants (N = 324) read a message that varied the introduction by providing a definition of genes that used either an "instruction" metaphor or a "blueprint" metaphor. The "instruction" metaphor compared to the "blueprint" metaphor promoted stronger threat perceptions, which aligned with both belief in the response efficacy of genetic research for health and perceived behavioral control linked to genes and health. The "blueprint" metaphor compared to the "instruction" metaphor promoted stronger essentialist beliefs, which aligned with more intense positive regard for the efficacy of genetic research and human health. Implications for health communicators include societal effects aligned with stigma and discrimination that such findings portend.

A systems biology approach reveals that tissue tropism to West Nile virus is regulated by antiviral genes and innate immune cellular processes

The actions of the RIG-I like receptor (RLR) and type I interferon (IFN) signaling pathways are essential for a protective innate immune response against the emerging flavivirus West Nile virus (WNV). In mice lacking RLR or IFN signaling pathways, WNV exhibits enhanced tissue tropism, indicating that specific host factors of innate immune defense restrict WNV infection and dissemination in peripheral tissues. However, the immune mechanisms by which the RLR and IFN pathways coordinate and function to impart restriction of WNV infection are not well defined. Using a systems biology approach, we defined the host innate immune response signature and actions that restrict WNV tissue tropism. Transcriptional profiling and pathway modeling to compare WNV-infected permissive (spleen) and nonpermissive (liver) tissues showed high enrichment for inflammatory responses, including pattern recognition receptors and IFN signaling pathways, that define restriction of WNV replication in the liver. Assessment of infected livers from Mavs^−/−×Ifnar^−/− mice revealed the loss of expression of several key components within the natural killer (NK) cell signaling pathway, including genes associated with NK cell activation, inflammatory cytokine production, and NK cell receptor signaling. In vivo analysis of hepatic immune cell infiltrates from WT mice demonstrated that WNV infection leads to an increase in NK cell numbers with enhanced proliferation, maturation, and effector action. In contrast, livers from Mavs^−/−×Ifnar^−/− infected mice displayed reduced immune cell infiltration, including a significant reduction in NK cell numbers. Analysis of cocultures of dendritic and NK cells revealed both cell-intrinsic and -extrinsic roles for the RLR and IFN signaling pathways to regulate NK cell effector activity. Taken together, these observations reveal a complex innate immune signaling network, regulated by the RLR and IFN signaling pathways, that drives tissue-specific antiviral effector gene expression and innate immune cellular processes that control tissue tropism to WNV infection.

West Nile virus (WNV), a mosquito-transmitted RNA flavivirus, is an NIAID Category B infectious agent that has emerged in the Western hemisphere as a serious public health threat. The innate immune effectors that impart restriction of WNV infection are not well defined. WNV infection is sensed by the host RIG-I like receptors (RLR), a class of pattern recognition receptors, to trigger type I interferon (IFN) and related innate immune defense programs. Using a systems biology approach, we evaluated the contribution of the RLR and type I IFN signaling pathways in controlling tissue tropism. WNV infection triggers tissue-specific innate immune responses, specifically antiviral effector genes and natural killer (NK) cell signaling related genes, which are directly regulated by the combined actions of the RLR and type I IFN signaling pathways. Cocultures of dendritic and NK cells revealed that RLR and type I IFN signaling pathways are essential in promoting NK cell activation during WNV infection. Our observations indicate that combined RLR- and type I IFN-dependent signaling programs drive specific antiviral effector gene expression and programs NK cell responses that, together, serve to restrict WNV tissue tropism.

Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes

To extend understanding of the genetic architecture and molecular basis of type 2 diabetes (T2D), we conducted a meta-analysis of genetic variants on the Metabochip, including 34,840 cases and 114,981 controls, overwhelmingly of European descent. We identified ten previously unreported T2D susceptibility loci, including two showing sex-differentiated association. Genome-wide analyses of these data are consistent with a long tail of additional common variant loci explaining much of the variation in susceptibility to T2D. Exploration of the enlarged set of susceptibility loci implicates several processes, including CREBBP-related transcription, adipocytokine signaling and cell cycle regulation, in diabetes pathogenesis.

Identification of RIFL, a novel adipocyte-enriched insulin target gene with a role in lipid metabolism

To identify new genes that are important in fat metabolism, we utilized the Lexicon-Genentech knockout database of genes encoding transmembrane and secreted factors and whole murine genome transcriptional profiling data that we generated for 3T3-L1 in vitro adipogenesis. Cross-referencing null models evidencing metabolic phenotypes with genes induced in adipogenesis led to identification of a new gene, which we named RIFL (refeeding induced fat and liver). RIFL-null mice have serum triglyceride levels approximately one-third of wild type. RIFL transcript is induced >100-fold during 3T3-L1 adipogenesis and is also increased markedly during adipogenesis of murine and human primary preadipocytes. siRNA-mediated knockdown of RIFL during 3T3-L1 adipogenesis results in an ~35% decrease in adipocyte triglyceride content. Murine RIFL transcript is highly enriched in white and brown adipose tissue and liver. Fractionation of WAT reveals that RIFL transcript is exclusive to adipocytes with a lack of expression in stromal-vascular cells. Nutritional and hormonal studies are consistent with a prolipogenic function for RIFL. There is evidence of an approximately eightfold increase in RIFL transcript level in WAT in ob/ob mice compared with wild-type mice. RIFL transcript level in WAT and liver is increased ~80- and 12-fold, respectively, following refeeding of fasted mice. Treatment of 3T3-L1 adipocytes with insulin increases RIFL transcript ≤35-fold, whereas agents that stimulate lipolysis downregulate RIFL. Interestingly, the 198-amino acid RIFL protein is predicted to be secreted and shows ~30% overall conservation with the NH(2)-terminal half of angiopoietin-like 3, a liver-secreted protein that impacts lipid metabolism. In summary, our data suggest that RIFL is an important new regulator of lipid metabolism.

First-degree relatives of type 2 diabetic patients have reduced expression of genes involved in fatty acid metabolism in skeletal muscle

CONTEXT

First-degree relatives of patients with type 2 diabetes (FH+) have been shown to have decreased energy expenditure and decreased expression of mitochondrial genes in skeletal muscle. In previous studies, it has been difficult to distinguish whether mitochondrial dysfunction and differential regulation of genes are primary (genetic) or due to reduced physical activity, obesity, or other correlated factors.

OBJECTIVE

The aim of this study was to investigate whether mitochondrial dysfunction is a primary defect or results from an altered metabolic state.

DESIGN

We compared gene expression in skeletal muscle from 24 male subjects with FH and 26 without FH matched for age, glucose tolerance, VO(2peak) (peak oxygen uptake), and body mass index using microarrays. Additionally, type fiber composition, mitochondrial DNA content, and citrate synthase activity were measured. The results were followed up in an additional cohort with measurements of in vivo metabolism.

RESULTS

FH+ vs. FH- subjects showed reduced expression of mitochondrial genes (P = 2.75 × 10(-6)), particularly genes involved in fatty acid metabolism (P = 4.08 × 10(-7)), despite similar mitochondrial DNA content. Strikingly, a 70% reduced expression of the monoamine oxidase A (MAOA) gene was found in FH+ vs. FH- individuals (P = 0.0009). Down-regulation of the genes involved in fat metabolism was associated with decreased in vivo fat oxidation and increased glucose oxidation examined in an additional cohort of elderly men.

CONCLUSIONS

These results suggest that genetically altered fatty acid metabolism predisposes to type 2 diabetes and propose a role for catecholamine-metabolizing enzymes like MAOA in the regulation of energy metabolism.

[Epigenetics, interface between environment and genes: role in complex diseases]

Epigenetics is the study of heritable changes in gene expression or cellular phenotype caused by mechanisms other than changes in the underlying DNA sequence. Epigenetics is one of the major mechanisms explaining the "Developmental Origin of Health and Diseases" (DOHaD). Besides genetic background inherited from parents, which confers susceptibility to certain pathologies, epigenetic changes constitute the memory of previous events, either positive or negative, along the life cycle, including at the in utero stage. The later exposition to hostile environment may reveal such susceptibility, with the development of various pathologies, among them numerous chronic complex diseases. The demonstration of such a sequence of events has been shown for metabolic diseases as obesity, metabolic syndrome and type 2 diabetes, cardiovascular disease and cancer. In contrast to genetic predisposition, which is irreversible, epigenetic changes are potentially reversible, thus giving targets not only for prevention, but possibly also for the treatment of certain complex diseases.

BAC-based sequencing of behaviorally-relevant genes in the prairie vole

The prairie vole (Microtus ochrogaster) is an important model organism for the study of social behavior, yet our ability to correlate genes and behavior in this species has been limited due to a lack of genetic and genomic resources. Here we report the BAC-based targeted sequencing of behaviorally-relevant genes and flanking regions in the prairie vole. A total of 6.4 Mb of non-redundant or haplotype-specific sequence assemblies were generated that span the partial or complete sequence of 21 behaviorally-relevant genes as well as an additional 55 flanking genes. Estimates of nucleotide diversity from 13 loci based on alignments of 1.7 Mb of haplotype-specific assemblies revealed an average pair-wise heterozygosity (8.4×10⁻³). Comparative analyses of the prairie vole proteins encoded by the behaviorally-relevant genes identified >100 substitutions specific to the prairie vole lineage. Finally, our sequencing data indicate that a duplication of the prairie vole AVPR1A locus likely originated from a recent segmental duplication spanning a minimum of 105 kb. In summary, the results of our study provide the genomic resources necessary for the molecular and genetic characterization of a high-priority set of candidate genes for regulating social behavior in the prairie vole.

Circulating anti-Mullerian hormone levels in adult men are under a strong genetic influence

CONTEXT

The determinants of serum anti-Müllerian hormone (AMH) levels in adult men remain unclear.

OBJECTIVE

The objective of the study was to investigate the genetic and environmental components in determining postpubertal AMH levels in healthy men.

DESIGN AND PARTICIPANTS

Serum AMH levels, body mass index (BMI), and fat mass (dual energy x-ray absorptiometry) were measured in 64 healthy male (23 monozygotic and 41 dizygotic) twin pairs.

RESULTS

Postpubertal AMH levels were highly genetically determined (broad sense heritability 0.92, 95% confidence interval 0.83-0.96). AMH correlated negatively with BMI (r = -0.26, P = 0.030) and fat mass (r = -0.23, P = 0.048). As AMH, BMI had a high heritability (0.68, 95% confidence interval 0.39-0.83), but no genetic correlation was observed between them.

CONCLUSIONS

AMH levels in men after puberty are under a strong genetic influence. Twin modeling suggests that AMH and BMI are influenced by different sets of genes.

Polycystic ovary syndrome in 2011: Genes, aging and sleep apnea in polycystic ovary syndrome

Polycystic ovary syndrome (PCOS) is a complex genetic disease that affects approximately 7% of women of reproductive age worldwide. From novel pathways implicated in the etiology of PCOS through genome-wide association to characterization of the reproductive and metabolic changes that occur in ageing women with PCOS, the year 2011 has seen a number of studies published that highlight the intricacies of this condition.

Selection of stable reference genes for quantitative rt-PCR comparisons of mouse embryonic and extra-embryonic stem cells

Isolation and culture of both embryonic and tissue specific stem cells provide an enormous opportunity to study the molecular processes driving development. To gain insight into the initial events underpinning mammalian embryogenesis, pluripotent stem cells from each of the three distinct lineages present within the preimplantation blastocyst have been derived. Embryonic (ES), trophectoderm (TS) and extraembryonic endoderm (XEN) stem cells possess the developmental potential of their founding lineages and seemingly utilize distinct epigenetic modalities to program gene expression. However, the basis for these differing cellular identities and epigenetic properties remain poorly defined.

Quantitative reverse transcription-polymerase chain reaction (qPCR) is a powerful and efficient means of rapidly comparing patterns of gene expression between different developmental stages and experimental conditions. However, careful, empirical selection of appropriate reference genes is essential to accurately measuring transcriptional differences. Here we report the quantitation and evaluation of fourteen commonly used references genes between ES, TS and XEN stem cells. These included: Actb, B2m, Hsp70, Gapdh, Gusb, H2afz, Hk2, Hprt, Pgk1, Ppia, Rn7sk, Sdha, Tbp and Ywhaz. Utilizing three independent statistical analysis, we identify Pgk1, Sdha and Tbp as the most stable reference genes between each of these stem cell types. Furthermore, we identify Sdha, Tbp and Ywhaz as well as Ywhaz, Pgk1 and Hk2 as the three most stable reference genes through the in vitro differentiation of embryonic and trophectoderm stem cells respectively.

Understanding the transcriptional and epigenetic regulatory mechanisms controlling cellular identity within these distinct stem cell types provides essential insight into cellular processes controlling both embryogenesis and stem cell biology. Normalizing quantitative RT-PCR measurements using the geometric mean CT values obtained for the identified mRNAs, offers a reliable method to assess differing patterns of gene expression between the three founding stem cell lineages present within the mammalian preimplantation embryo.

Prediction of disease and phenotype associations from genome-wide association studies

BACKGROUND

Genome wide association studies (GWAS) have proven useful as a method for identifying genetic variations associated with diseases. In this study, we analyzed GWAS data for 61 diseases and phenotypes to elucidate common associations based on single nucleotide polymorphisms (SNP). The study was an expansion on a previous study on identifying disease associations via data from a single GWAS on seven diseases.

METHODOLOGY/PRINCIPAL FINDINGS

Adjustments to the originally reported study included expansion of the SNP dataset using Linkage Disequilibrium (LD) and refinement of the four levels of analysis to encompass SNP, SNP block, gene, and pathway level comparisons. A pair-wise comparison between diseases and phenotypes was performed at each level and the Jaccard similarity index was used to measure the degree of association between two diseases/phenotypes. Disease relatedness networks (DRNs) were used to visualize our results. We saw predominant relatedness between Multiple Sclerosis, type 1 diabetes, and rheumatoid arthritis for the first three levels of analysis. Expected relatedness was also seen between lipid- and blood-related traits.

CONCLUSIONS/SIGNIFICANCE

The predominant associations between Multiple Sclerosis, type 1 diabetes, and rheumatoid arthritis can be validated by clinical studies. The diseases have been proposed to share a systemic inflammation phenotype that can result in progression of additional diseases in patients with one of these three diseases. We also noticed unexpected relationships between metabolic and neurological diseases at the pathway comparison level. The less significant relationships found between diseases require a more detailed literature review to determine validity of the predictions. The results from this study serve as a first step towards a better understanding of seemingly unrelated diseases and phenotypes with similar symptoms or modes of treatment.

Molecular cloning, expression, and imprinting status of maternally expressed gene 8 (Meg8) in dairy cattle

At present, small number imprinted genes have been reported in cattle compare to human and mouse. Maternally expressed gene 8 (Meg8), a non-coding gene, have been identified maternally expressed in mouse and sheep, but its sequences and imprinting status have not been established in cattle. In this study, the full-length of cattle Meg8cDNA sequence was obtained by reverse transcript polymerase chain reaction (RT-PCR) and rapid amplification of cDNA ends (RACE) method, which has a high homology in exons sequences with the corresponding region of sheep Meg8. The isolation of cDNA sequence showed the presence of multiple splice variants in cattle Meg8 gene. The Meg8 was found to be expressed in all adult examined tissues, including heart, liver, spleen, lung, kidney, brain, subcutaneous fat and skeletal muscle. A single nucleotide polymorphism (SNP) was identified in exon 6 by Single-Strand Conformation Polymorphism (SSCP), and used to distinguish between monoallelic and biallelic expression in cattle tissues. The expression analysis of Meg8 in a heterozygous cattle showed that only one parental allele was expressed in all examined tissues, suggesting that Meg8 is imprinted in cattle.

Molecular identification of genes involved in testicular steroid synthesis and characterization of the response to gonadotropic stimulation in the Senegalese sole (Solea senegalensis) testis

In male teleosts, testicular steroids are essential hormones for the regulation of spermatogenesis and their production is regulated by pituitary gonadotropins. In the Senegalese sole (Solea senegalensis), an economically important flatfish with semi-cystic and asynchronous spermatogenesis, the gonadotropic regulation of spermatogenesis, particularly regarding the production and regulation of testicular steroids, are not well understood. For this reason, we first cloned and characterized the response of several key genes for the production and action of testicular steroids to the in vivo administration of human chorionic gonadotropin (hCG) and, second, we investigated the transcriptomic effects of hCG in the Senegalese sole testis. We succeeded in cloning the full-length cDNAs for Steroidogenic Acute Regulatory protein (StAR), 3β-hydroxysteroid dehydrogenase (3β-HSD), 17β-HSD and 20β-HSD and a partial cDNA for the nuclear progesterone receptor. In this study we also identified a transcript encoding a protein with homology to StAR, which we named StAR-like, that could represent a new member of the StAR-related lipid transfer (START) family. All the cloned genes were expressed in the testis and their expression levels were significantly increased by the in vivo administration of hCG. The plasma levels of testosterone and 11-ketotestosterone also increased in response to hCG administration, likely as a result of the induction of the expression of steroidogenic enzymes by hCG. Furthermore, gene expression analysis by microarray identified 90 differentially expressed genes in the testis in response to hCG administration, including genes potentially involved in steroidogenesis, progression of spermatogenesis and germ cell maturation and cytoskeletal organization. Our results have identified for the first time a number of key genes involved in the regulation of steroid production and spermatogenesis in the Senegalese sole testis that are under gonadotropic control.

Pancreatic islet-specific overexpression of Reg3β protein induced the expression of pro-islet genes and protected the mice against streptozotocin-induced diabetes mellitus

Reg family proteins have been implicated in islet β-cell proliferation, survival, and regeneration. The expression of Reg3β (pancreatitis-associated protein) is highly induced in experimental diabetes and acute pancreatitis, but its precise role has not been established. Through knockout studies, this protein was shown to be mitogenic, antiapoptotic, and anti-inflammatory in the liver and pancreatic acinars. To test whether it can promote islet cell growth or survival against experimental damage, we developed β-cell-specific overexpression using rat insulin I promoter, evaluated the changes in normal islet function, gene expression profile, and the response to streptozotocin-induced diabetes. Significant and specific overexpression of Reg3β was achieved in the pancreatic islets of RIP-I/Reg3β mice, which exhibited normal islet histology, β-cell mass, and in vivo and in vitro insulin secretion in response to high glucose yet were slightly hyperglycemic and low in islet GLUT2 level. Upon streptozotocin treatment, in contrast to wild-type littermates that became hyperglycemic in 3 days and lost 15% of their weight, RIP-I/Reg3β mice were significantly protected from hyperglycemia and weight loss. To identify specific targets affected by Reg3β overexpression, a whole genome DNA microarray on islet RNA isolated from the transgenic mice revealed more than 45 genes significantly either up- or downregulated. Among them, islet-protective osteopontin/SPP1 and acute responsive nuclear protein p8/NUPR1 were significantly induced, a result further confirmed by real-time PCR, Western blots, and immunohistochemistry. Our results suggest that Reg3β is unlikely an islet growth factor but a putative protector that prevents streptozotocin-induced damage by inducing the expression of specific genes.

Identification of reference genes across physiological states for qRT-PCR through microarray meta-analysis

Background

The accuracy of quantitative real-time PCR (qRT-PCR) is highly dependent on reliable reference gene(s). Some housekeeping genes which are commonly used for normalization are widely recognized as inappropriate in many experimental conditions. This study aimed to identify reference genes for clinical studies through microarray meta-analysis of human clinical samples.

Methodology/Principal Findings

After uniform data preprocessing and data quality control, 4,804 Affymetrix HU-133A arrays performed by clinical samples were classified into four physiological states with 13 organ/tissue types. We identified a list of reference genes for each organ/tissue types which exhibited stable expression across physiological states. Furthermore, 102 genes identified as reference gene candidates in multiple organ/tissue types were selected for further analysis. These genes have been frequently identified as housekeeping genes in previous studies, and approximately 71% of them fall into Gene Expression (GO:0010467) category in Gene Ontology.

Conclusions/Significance

Based on microarray meta-analysis of human clinical sample arrays, we identified sets of reference gene candidates for various organ/tissue types and then examined the functions of these genes. Additionally, we found that many of the reference genes are functionally related to transcription, RNA processing and translation. According to our results, researchers could select single or multiple reference gene(s) for normalization of qRT-PCR in clinical studies.

Homeostasis, Part 1. Homeostasis versus homeodynamism

All nurses are familiar with the term 'normal', where it concerns the range of figures recorded during assessments and observations of body fluids and organ functioning. Many are familiar with the concept of homeostasis. However, few have heard of 'homeodynamism', which may be a more appropriate term. This article, the first in a series of six, defines this. It introduces the principles of homeostasis and looks at it at cellular, tissue, organ and system levels. After reading this article, the nurse should be able to: relate the principles of homeostatic theory to health and illness; know why and how systemic integration is fundamental to the maintenance of intracellular metabolic homeostasis; acknowledge that cells are the basic unit of health, illness and healthcare intervention; and appreciate that receptors, enzymes and adenosine triphosphate are the key chemicals of a healthy metabolism.

Nonsyndromic cleft lip and palate: CRISPLD genes and the folate gene pathway connection

BACKGROUND

Nonsyndromic cleft lip with or without cleft palate (NSCLP) is a common birth defect that has a multifactorial etiology. Despite having substantial genetic liability, <15% of the genetic contribution to NSCLP has been delineated. In our efforts to dissect the genetics of NSCLP, we found that variation in the CRISPLD2 (cysteine-rich secretory protein LCCL domain containing 2) gene is associated with NSCLP and that the protein is expressed in the developing murine craniofacies. In addition, we found suggestive linkage of NSCLP (LOD > 1.0) to the chromosomal region on 8q13.2-21.13 that contains the CRISPLD1 gene. The protein products of both CRISPLD1 and CRISPLD2 contain more cysteine residues than comparably sized proteins. Interestingly, the folic acid pathway produces endogenous cysteines, and variation in genes in this pathway is associated with NSCLP. Based on these observations, we hypothesized that variation in CRISPLD1 contributes to NSCLP and that both CRISPLD genes interact with each other and genes in the folic acid pathway.

METHODS

Single nucleotide polymorphisms (SNPs) in CRISPLD1 were genotyped in our non-Hispanic white and Hispanic multiplex and simplex NSCLP families.

RESULTS

There was little evidence for a role of variation for CRISPLD1 alone in NSCLP. However, interactions were detected between CRISPLD1/CRISPLD2 SNPs and variation in folate pathway genes. Altered transmission of one CRISPLD1 SNP was detected in the NHW simplex families. Importantly, interactions were detected between SNPs in CRISPLD1 and CRISPLD2 (15 interactions, 0.0031 ≤p < 0.05).

CONCLUSION

These novel findings suggest that CRISPLD1 plays a role in NSCLP through the interaction with CRISPLD2 and folate pathway genes.

A general framework for analyzing data from two short time-series microarray experiments

We propose a general theoretical framework for analyzing differentially expressed genes and behavior patterns from two homogenous short time-course data. The framework generalizes the recently proposed Hilbert-Schmidt Independence Criterion (HSIC)-based framework adapting it to the time-series scenario by utilizing tensor analysis for data transformation. The proposed framework is effective in yielding criteria that can identify both the differentially expressed genes and time-course patterns of interest between two time-series experiments without requiring to explicitly cluster the data. The results, obtained by applying the proposed framework with a linear kernel formulation, on various data sets are found to be both biologically meaningful and consistent with published studies.