Method for determining gene knockouts

DOEpatents

Maranas, Costa D; Burgard, Anthony R; Pharkya, Priti

2013-06-04

A method for determining candidates for gene deletions and additions using a model of a metabolic network associated with an organism, the model includes a plurality of metabolic reactions defining metabolite relationships, the method includes selecting a bioengineering objective for the organism, selecting at least one cellular objective, forming an optimization problem that couples the at least one cellular objective with the bioengineering objective, and solving the optimization problem to yield at least one candidate.

Constructing an integrated gene similarity network for the identification of disease genes.

PubMed

Tian, Zhen; Guo, Maozu; Wang, Chunyu; Xing, LinLin; Wang, Lei; Zhang, Yin

2017-09-20

Discovering novel genes that are involved human diseases is a challenging task in biomedical research. In recent years, several computational approaches have been proposed to prioritize candidate disease genes. Most of these methods are mainly based on protein-protein interaction (PPI) networks. However, since these PPI networks contain false positives and only cover less half of known human genes, their reliability and coverage are very low. Therefore, it is highly necessary to fuse multiple genomic data to construct a credible gene similarity network and then infer disease genes on the whole genomic scale. We proposed a novel method, named RWRB, to infer causal genes of interested diseases. First, we construct five individual gene (protein) similarity networks based on multiple genomic data of human genes. Then, an integrated gene similarity network (IGSN) is reconstructed based on similarity network fusion (SNF) method. Finally, we employee the random walk with restart algorithm on the phenotype-gene bilayer network, which combines phenotype similarity network, IGSN as well as phenotype-gene association network, to prioritize candidate disease genes. We investigate the effectiveness of RWRB through leave-one-out cross-validation methods in inferring phenotype-gene relationships. Results show that RWRB is more accurate than state-of-the-art methods on most evaluation metrics. Further analysis shows that the success of RWRB is benefited from IGSN which has a wider coverage and higher reliability comparing with current PPI networks. Moreover, we conduct a comprehensive case study for Alzheimer's disease and predict some novel disease genes that supported by literature. RWRB is an effective and reliable algorithm in prioritizing candidate disease genes on the genomic scale. Software and supplementary information are available at http://nclab.hit.edu.cn/~tianzhen/RWRB/ .

Convergence of GWA and candidate gene studies for alcoholism

PubMed Central

Olfson, Emily; Bierut, Laura Jean

2012-01-01

Background Genome-wide association (GWA) studies have led to a paradigm shift in how researchers study the genetics underlying disease. Many GWA studies are now publicly available and can be used to examine whether or not previously proposed candidate genes are supported by GWA data. This approach is particularly important for the field of alcoholism because the contribution of many candidate genes remains controversial. Methods Using the Human Genome Epidemiology (HuGE) Navigator, we selected candidate genes for alcoholism that have been frequently examined in scientific articles in the past decade. Specific candidate loci as well as all the reported SNPs in candidate genes were examined in the Study of Alcohol Addiction: Genetics and Addiction (SAGE), a GWA study comparing alcohol dependent and non-dependent subjects. Results Several commonly reported candidate loci, including rs1800497 in DRD2, rs698 in ADH1C, rs1799971 in OPRM1 and rs4680 in COMT, are not replicated in SAGE (p> .05). Among candidate loci available for analysis, only rs279858 in GABRA2 (p=0.0052, OR=1.16) demonstrated a modest association. Examination of all SNPs reported in SAGE in over 50 candidate genes revealed no SNPs with large frequency differences between cases and controls and the lowest p value of any SNP was .0006. Discussion We provide evidence that several extensively studied candidate loci do not have a strong contribution to risk of developing alcohol dependence in European and African Ancestry populations. Due to lack of coverage, we were unable to rule out the contribution of other variants and these genes and particular loci warrant further investigation. Our analysis demonstrates that publicly available GWA results can be used to better understand which if any of previously proposed candidate genes contribute to disease. Furthermore, we illustrate how examining the convergence of candidate gene and GWA studies can help elucidate the genetic architecture of alcoholism and more generally complex diseases. PMID:22978509

Identifying candidate drivers of drug response in heterogeneous cancer by mining high throughput genomics data.

PubMed

Nabavi, Sheida

2016-08-15

With advances in technologies, huge amounts of multiple types of high-throughput genomics data are available. These data have tremendous potential to identify new and clinically valuable biomarkers to guide the diagnosis, assessment of prognosis, and treatment of complex diseases, such as cancer. Integrating, analyzing, and interpreting big and noisy genomics data to obtain biologically meaningful results, however, remains highly challenging. Mining genomics datasets by utilizing advanced computational methods can help to address these issues. To facilitate the identification of a short list of biologically meaningful genes as candidate drivers of anti-cancer drug resistance from an enormous amount of heterogeneous data, we employed statistical machine-learning techniques and integrated genomics datasets. We developed a computational method that integrates gene expression, somatic mutation, and copy number aberration data of sensitive and resistant tumors. In this method, an integrative method based on module network analysis is applied to identify potential driver genes. This is followed by cross-validation and a comparison of the results of sensitive and resistance groups to obtain the final list of candidate biomarkers. We applied this method to the ovarian cancer data from the cancer genome atlas. The final result contains biologically relevant genes, such as COL11A1, which has been reported as a cis-platinum resistant biomarker for epithelial ovarian carcinoma in several recent studies. The described method yields a short list of aberrant genes that also control the expression of their co-regulated genes. The results suggest that the unbiased data driven computational method can identify biologically relevant candidate biomarkers. It can be utilized in a wide range of applications that compare two conditions with highly heterogeneous datasets.

ProDiGe: Prioritization Of Disease Genes with multitask machine learning from positive and unlabeled examples

PubMed Central

2011-01-01

Background Elucidating the genetic basis of human diseases is a central goal of genetics and molecular biology. While traditional linkage analysis and modern high-throughput techniques often provide long lists of tens or hundreds of disease gene candidates, the identification of disease genes among the candidates remains time-consuming and expensive. Efficient computational methods are therefore needed to prioritize genes within the list of candidates, by exploiting the wealth of information available about the genes in various databases. Results We propose ProDiGe, a novel algorithm for Prioritization of Disease Genes. ProDiGe implements a novel machine learning strategy based on learning from positive and unlabeled examples, which allows to integrate various sources of information about the genes, to share information about known disease genes across diseases, and to perform genome-wide searches for new disease genes. Experiments on real data show that ProDiGe outperforms state-of-the-art methods for the prioritization of genes in human diseases. Conclusions ProDiGe implements a new machine learning paradigm for gene prioritization, which could help the identification of new disease genes. It is freely available at http://cbio.ensmp.fr/prodige. PMID:21977986

Defining the Human Macula Transcriptome and Candidate Retinal Disease Genes UsingEyeSAGE

PubMed Central

Rickman, Catherine Bowes; Ebright, Jessica N.; Zavodni, Zachary J.; Yu, Ling; Wang, Tianyuan; Daiger, Stephen P.; Wistow, Graeme; Boon, Kathy; Hauser, Michael A.

2009-01-01

Purpose To develop large-scale, high-throughput annotation of the human macula transcriptome and to identify and prioritize candidate genes for inherited retinal dystrophies, based on ocular-expression profiles using serial analysis of gene expression (SAGE). Methods Two human retina and two retinal pigment epithelium (RPE)/choroid SAGE libraries made from matched macula or midperipheral retina and adjacent RPE/choroid of morphologically normal 28- to 66-year-old donors and a human central retina longSAGE library made from 41- to 66-year-old donors were generated. Their transcription profiles were entered into a relational database, EyeSAGE, including microarray expression profiles of retina and publicly available normal human tissue SAGE libraries. EyeSAGE was used to identify retina- and RPE-specific and -associated genes, and candidate genes for retina and RPE disease loci. Differential and/or cell-type specific expression was validated by quantitative and single-cell RT-PCR. Results Cone photoreceptor-associated gene expression was elevated in the macula transcription profiles. Analysis of the longSAGE retina tags enhanced tag-to-gene mapping and revealed alternatively spliced genes. Analysis of candidate gene expression tables for the identified Bardet-Biedl syndrome disease gene (BBS5) in the BBS5 disease region table yielded BBS5 as the top candidate. Compelling candidates for inherited retina diseases were identified. Conclusions The EyeSAGE database, combining three different gene-profiling platforms including the authors’ multidonor-derived retina/RPE SAGE libraries and existing single-donor retina/RPE libraries, is a powerful resource for definition of the retina and RPE transcriptomes. It can be used to identify retina-specific genes, including alternatively spliced transcripts and to prioritize candidate genes within mapped retinal disease regions. PMID:16723438

Disease gene prioritization by integrating tissue-specific molecular networks using a robust multi-network model.

PubMed

Ni, Jingchao; Koyuturk, Mehmet; Tong, Hanghang; Haines, Jonathan; Xu, Rong; Zhang, Xiang

2016-11-10

Accurately prioritizing candidate disease genes is an important and challenging problem. Various network-based methods have been developed to predict potential disease genes by utilizing the disease similarity network and molecular networks such as protein interaction or gene co-expression networks. Although successful, a common limitation of the existing methods is that they assume all diseases share the same molecular network and a single generic molecular network is used to predict candidate genes for all diseases. However, different diseases tend to manifest in different tissues, and the molecular networks in different tissues are usually different. An ideal method should be able to incorporate tissue-specific molecular networks for different diseases. In this paper, we develop a robust and flexible method to integrate tissue-specific molecular networks for disease gene prioritization. Our method allows each disease to have its own tissue-specific network(s). We formulate the problem of candidate gene prioritization as an optimization problem based on network propagation. When there are multiple tissue-specific networks available for a disease, our method can automatically infer the relative importance of each tissue-specific network. Thus it is robust to the noisy and incomplete network data. To solve the optimization problem, we develop fast algorithms which have linear time complexities in the number of nodes in the molecular networks. We also provide rigorous theoretical foundations for our algorithms in terms of their optimality and convergence properties. Extensive experimental results show that our method can significantly improve the accuracy of candidate gene prioritization compared with the state-of-the-art methods. In our experiments, we compare our methods with 7 popular network-based disease gene prioritization algorithms on diseases from Online Mendelian Inheritance in Man (OMIM) database. The experimental results demonstrate that our methods recover true associations more accurately than other methods in terms of AUC values, and the performance differences are significant (with paired t-test p-values less than 0.05). This validates the importance to integrate tissue-specific molecular networks for studying disease gene prioritization and show the superiority of our network models and ranking algorithms toward this purpose. The source code and datasets are available at http://nijingchao.github.io/CRstar/ .

Identification of downy mildew resistance gene candidates by positional cloning in maize (Zea mays subsp. mays; Poaceae)1

PubMed Central

Kim, Jae Yoon; Moon, Jun-Cheol; Kim, Hyo Chul; Shin, Seungho; Song, Kitae; Kim, Kyung-Hee; Lee, Byung-Moo

2017-01-01

Premise of the study: Positional cloning in combination with phenotyping is a general approach to identify disease-resistance gene candidates in plants; however, it requires several time-consuming steps including population or fine mapping. Therefore, in the present study, we suggest a new combined strategy to improve the identification of disease-resistance gene candidates. Methods and Results: Downy mildew (DM)–resistant maize was selected from five cultivars using a spreader row technique. Positional cloning and bioinformatics tools were used to identify the DM-resistance quantitative trait locus marker (bnlg1702) and 47 protein-coding gene annotations. Eventually, five DM-resistance gene candidates, including bZIP34, Bak1, and Ppr, were identified by quantitative reverse-transcription PCR (RT-PCR) without fine mapping of the bnlg1702 locus. Conclusions: The combined protocol with the spreader row technique, quantitative trait locus positional cloning, and quantitative RT-PCR was effective for identifying DM-resistance candidate genes. This cloning approach may be applied to other whole-genome-sequenced crops or resistance to other diseases. PMID:28224059

Looking into flowering time in almond (Prunus dulcis (Mill) D. A. Webb): the candidate gene approach.

PubMed

Silva, C; Garcia-Mas, J; Sánchez, A M; Arús, P; Oliveira, M M

2005-03-01

Blooming time is one of the most important agronomic traits in almond. Biochemical and molecular events underlying flowering regulation must be understood before methods to stimulate late flowering can be developed. Attempts to elucidate the genetic control of this process have led to the identification of a major gene (Lb) and quantitative trait loci (QTLs) linked to observed phenotypic differences, but although this gene and these QTLs have been placed on the Prunus reference genetic map, their sequences and specific functions remain unknown. The aim of our investigation was to associate these loci with known genes using a candidate gene approach. Two almond cDNAs and eight Prunus expressed sequence tags were selected as candidate genes (CGs) since their sequences were highly identical to those of flowering regulatory genes characterized in other species. The CGs were amplified from both parental lines of the mapping population using specific primers. Sequence comparison revealed DNA polymorphisms between the parental lines, mainly of the single nucleotide type. Polymorphisms were used to develop co-dominant cleaved amplified polymorphic sequence markers or length polymorphisms based on insertion/deletion events for mapping the candidate genes on the Prunus reference map. Ten candidate genes were assigned to six linkage groups in the Prunus genome. The positions of two of these were compatible with the regions where two QTLs for blooming time were detected. One additional candidate was localized close to the position of the Evergrowing gene, which determines a non-deciduous behaviour in peach.

Leveraging lung tissue transcriptome to uncover candidate causal genes in COPD genetic associations.

PubMed

Lamontagne, Maxime; Bérubé, Jean-Christophe; Obeidat, Ma'en; Cho, Michael H; Hobbs, Brian D; Sakornsakolpat, Phuwanat; de Jong, Kim; Boezen, H Marike; Nickle, David; Hao, Ke; Timens, Wim; van den Berge, Maarten; Joubert, Philippe; Laviolette, Michel; Sin, Don D; Paré, Peter D; Bossé, Yohan

2018-05-15

Causal genes of chronic obstructive pulmonary disease (COPD) remain elusive. The current study aims at integrating genome-wide association studies (GWAS) and lung expression quantitative trait loci (eQTL) data to map COPD candidate causal genes and gain biological insights into the recently discovered COPD susceptibility loci. Two complementary genomic datasets on COPD were studied. First, the lung eQTL dataset which included whole-genome gene expression and genotyping data from 1038 individuals. Second, the largest COPD GWAS to date from the International COPD Genetics Consortium (ICGC) with 13 710 cases and 38 062 controls. Methods that integrated GWAS with eQTL signals including transcriptome-wide association study (TWAS), colocalization and Mendelian randomization-based (SMR) approaches were used to map causality genes, i.e. genes with the strongest evidence of being the functional effector at specific loci. These methods were applied at the genome-wide level and at COPD risk loci derived from the GWAS literature. Replication was performed using lung data from GTEx. We collated 129 non-overlapping risk loci for COPD from the GWAS literature. At the genome-wide scale, 12 new COPD candidate genes/loci were revealed and six replicated in GTEx including CAMK2A, DMPK, MYO15A, TNFRSF10A, BTN3A2 and TRBV30. In addition, we mapped candidate causal genes for 60 out of the 129 GWAS-nominated loci and 23 of them were replicated in GTEx. Mapping candidate causal genes in lung tissue represents an important contribution to the genetics of COPD, enriches our biological interpretation of GWAS findings, and brings us closer to clinical translation of genetic associations.

A Candidate Gene Analysis of Methylphenidate Response in Attention-Deficit/Hyperactivity Disorder

ERIC Educational Resources Information Center

McGough, James J.; McCracken, James T.; Loo, Sandra K.; Manganiello, Marc; Leung, Michael C.; Tietjens, Jeremy R.; Trinh, Thao; Baweja, Shilpa; Suddath, Robert; Smalley, Susan L.; Hellemann, Gerhard; Sugar, Catherine A.

2009-01-01

Objective: This study examines the potential role of candidate genes in moderating treatment effects of methylphenidate (MPH) in attention-deficit/hyperactivity disorder (ADHD). Method: Eighty-two subjects with ADHD aged 6 to 17 years participated in a prospective, double-blind, placebo-controlled, multiple-dose, crossover titration trial of…

Annotating novel genes by integrating synthetic lethals and genomic information

PubMed Central

Schöner, Daniel; Kalisch, Markus; Leisner, Christian; Meier, Lukas; Sohrmann, Marc; Faty, Mahamadou; Barral, Yves; Peter, Matthias; Gruissem, Wilhelm; Bühlmann, Peter

2008-01-01

Background Large scale screening for synthetic lethality serves as a common tool in yeast genetics to systematically search for genes that play a role in specific biological processes. Often the amounts of data resulting from a single large scale screen far exceed the capacities of experimental characterization of every identified target. Thus, there is need for computational tools that select promising candidate genes in order to reduce the number of follow-up experiments to a manageable size. Results We analyze synthetic lethality data for arp1 and jnm1, two spindle migration genes, in order to identify novel members in this process. To this end, we use an unsupervised statistical method that integrates additional information from biological data sources, such as gene expression, phenotypic profiling, RNA degradation and sequence similarity. Different from existing methods that require large amounts of synthetic lethal data, our method merely relies on synthetic lethality information from two single screens. Using a Multivariate Gaussian Mixture Model, we determine the best subset of features that assign the target genes to two groups. The approach identifies a small group of genes as candidates involved in spindle migration. Experimental testing confirms the majority of our candidates and we present she1 (YBL031W) as a novel gene involved in spindle migration. We applied the statistical methodology also to TOR2 signaling as another example. Conclusion We demonstrate the general use of Multivariate Gaussian Mixture Modeling for selecting candidate genes for experimental characterization from synthetic lethality data sets. For the given example, integration of different data sources contributes to the identification of genetic interaction partners of arp1 and jnm1 that play a role in the same biological process. PMID:18194531

Discovery of new candidate genes related to brain development using protein interaction information.

PubMed

Chen, Lei; Chu, Chen; Kong, Xiangyin; Huang, Tao; Cai, Yu-Dong

2015-01-01

Human brain development is a dramatic process composed of a series of complex and fine-tuned spatiotemporal gene expressions. A good comprehension of this process can assist us in developing the potential of our brain. However, we have only limited knowledge about the genes and gene functions that are involved in this biological process. Therefore, a substantial demand remains to discover new brain development-related genes and identify their biological functions. In this study, we aimed to discover new brain-development related genes by building a computational method. We referred to a series of computational methods used to discover new disease-related genes and developed a similar method. In this method, the shortest path algorithm was executed on a weighted graph that was constructed using protein-protein interactions. New candidate genes fell on at least one of the shortest paths connecting two known genes that are related to brain development. A randomization test was then adopted to filter positive discoveries. Of the final identified genes, several have been reported to be associated with brain development, indicating the effectiveness of the method, whereas several of the others may have potential roles in brain development.

Candidate gene prioritization by network analysis of differential expression using machine learning approaches

PubMed Central

2010-01-01

Background Discovering novel disease genes is still challenging for diseases for which no prior knowledge - such as known disease genes or disease-related pathways - is available. Performing genetic studies frequently results in large lists of candidate genes of which only few can be followed up for further investigation. We have recently developed a computational method for constitutional genetic disorders that identifies the most promising candidate genes by replacing prior knowledge by experimental data of differential gene expression between affected and healthy individuals. To improve the performance of our prioritization strategy, we have extended our previous work by applying different machine learning approaches that identify promising candidate genes by determining whether a gene is surrounded by highly differentially expressed genes in a functional association or protein-protein interaction network. Results We have proposed three strategies scoring disease candidate genes relying on network-based machine learning approaches, such as kernel ridge regression, heat kernel, and Arnoldi kernel approximation. For comparison purposes, a local measure based on the expression of the direct neighbors is also computed. We have benchmarked these strategies on 40 publicly available knockout experiments in mice, and performance was assessed against results obtained using a standard procedure in genetics that ranks candidate genes based solely on their differential expression levels (Simple Expression Ranking). Our results showed that our four strategies could outperform this standard procedure and that the best results were obtained using the Heat Kernel Diffusion Ranking leading to an average ranking position of 8 out of 100 genes, an AUC value of 92.3% and an error reduction of 52.8% relative to the standard procedure approach which ranked the knockout gene on average at position 17 with an AUC value of 83.7%. Conclusion In this study we could identify promising candidate genes using network based machine learning approaches even if no knowledge is available about the disease or phenotype. PMID:20840752

Leveraging multiple gene networks to prioritize GWAS candidate genes via network representation learning.

PubMed

Wu, Mengmeng; Zeng, Wanwen; Liu, Wenqiang; Lv, Hairong; Chen, Ting; Jiang, Rui

2018-06-03

Genome-wide association studies (GWAS) have successfully discovered a number of disease-associated genetic variants in the past decade, providing an unprecedented opportunity for deciphering genetic basis of human inherited diseases. However, it is still a challenging task to extract biological knowledge from the GWAS data, due to such issues as missing heritability and weak interpretability. Indeed, the fact that the majority of discovered loci fall into noncoding regions without clear links to genes has been preventing the characterization of their functions and appealing for a sophisticated approach to bridge genetic and genomic studies. Towards this problem, network-based prioritization of candidate genes, which performs integrated analysis of gene networks with GWAS data, has emerged as a promising direction and attracted much attention. However, most existing methods overlook the sparse and noisy properties of gene networks and thus may lead to suboptimal performance. Motivated by this understanding, we proposed a novel method called REGENT for integrating multiple gene networks with GWAS data to prioritize candidate genes for complex diseases. We leveraged a technique called the network representation learning to embed a gene network into a compact and robust feature space, and then designed a hierarchical statistical model to integrate features of multiple gene networks with GWAS data for the effective inference of genes associated with a disease of interest. We applied our method to six complex diseases and demonstrated the superior performance of REGENT over existing approaches in recovering known disease-associated genes. We further conducted a pathway analysis and showed that the ability of REGENT to discover disease-associated pathways. We expect to see applications of our method to a broad spectrum of diseases for post-GWAS analysis. REGENT is freely available at https://github.com/wmmthu/REGENT. Copyright © 2018 Elsevier Inc. All rights reserved.

NDRC: A Disease-Causing Genes Prioritized Method Based on Network Diffusion and Rank Concordance.

PubMed

Fang, Minghong; Hu, Xiaohua; Wang, Yan; Zhao, Junmin; Shen, Xianjun; He, Tingting

2015-07-01

Disease-causing genes prioritization is very important to understand disease mechanisms and biomedical applications, such as design of drugs. Previous studies have shown that promising candidate genes are mostly ranked according to their relatedness to known disease genes or closely related disease genes. Therefore, a dangling gene (isolated gene) with no edges in the network can not be effectively prioritized. These approaches tend to prioritize those genes that are highly connected in the PPI network while perform poorly when they are applied to loosely connected disease genes. To address these problems, we propose a new disease-causing genes prioritization method that based on network diffusion and rank concordance (NDRC). The method is evaluated by leave-one-out cross validation on 1931 diseases in which at least one gene is known to be involved, and it is able to rank the true causal gene first in 849 of all 2542 cases. The experimental results suggest that NDRC significantly outperforms other existing methods such as RWR, VAVIEN, DADA and PRINCE on identifying loosely connected disease genes and successfully put dangling genes as potential candidate disease genes. Furthermore, we apply NDRC method to study three representative diseases, Meckel syndrome 1, Protein C deficiency and Peroxisome biogenesis disorder 1A (Zellweger). Our study has also found that certain complex disease-causing genes can be divided into several modules that are closely associated with different disease phenotype.

Development of New Candidate Gene and EST-Based Molecular Markers for Gossypium Species

PubMed Central

Buyyarapu, Ramesh; Kantety, Ramesh V.; Yu, John Z.; Saha, Sukumar; Sharma, Govind C.

2011-01-01

New source of molecular markers accelerate the efforts in improving cotton fiber traits and aid in developing high-density integrated genetic maps. We developed new markers based on candidate genes and G. arboreum EST sequences that were used for polymorphism detection followed by genetic and physical mapping. Nineteen gene-based markers were surveyed for polymorphism detection in 26 Gossypium species. Cluster analysis generated a phylogenetic tree with four major sub-clusters for 23 species while three species branched out individually. CAP method enhanced the rate of polymorphism of candidate gene-based markers between G. hirsutum and G. barbadense. Two hundred A-genome based SSR markers were designed after datamining of G. arboreum EST sequences (Mississippi Gossypium arboreum   EST-SSR: MGAES). Over 70% of MGAES markers successfully produced amplicons while 65 of them demonstrated polymorphism between the parents of G. hirsutum and G. barbadense RIL population and formed 14 linkage groups. Chromosomal localization of both candidate gene-based and MGAES markers was assisted by euploid and hypoaneuploid CS-B analysis. Gene-based and MGAES markers were highly informative as they were designed from candidate genes and fiber transcriptome with a potential to be integrated into the existing cotton genetic and physical maps. PMID:22315588

Comparative analysis of protein interactome networks prioritizes candidate genes with cancer signatures.

PubMed

Li, Yongsheng; Sahni, Nidhi; Yi, Song

2016-11-29

Comprehensive understanding of human cancer mechanisms requires the identification of a thorough list of cancer-associated genes, which could serve as biomarkers for diagnoses and therapies in various types of cancer. Although substantial progress has been made in functional studies to uncover genes involved in cancer, these efforts are often time-consuming and costly. Therefore, it remains challenging to comprehensively identify cancer candidate genes. Network-based methods have accelerated this process through the analysis of complex molecular interactions in the cell. However, the extent to which various interactome networks can contribute to prediction of candidate genes responsible for cancer is still enigmatic. In this study, we evaluated different human protein-protein interactome networks and compared their application to cancer gene prioritization. Our results indicate that network analyses can increase the power to identify novel cancer genes. In particular, such predictive power can be enhanced with the use of unbiased systematic protein interaction maps for cancer gene prioritization. Functional analysis reveals that the top ranked genes from network predictions co-occur often with cancer-related terms in literature, and further, these candidate genes are indeed frequently mutated across cancers. Finally, our study suggests that integrating interactome networks with other omics datasets could provide novel insights into cancer-associated genes and underlying molecular mechanisms.

Selection of reference genes for miRNA qRT-PCR under abiotic stress in grapevine.

PubMed

Luo, Meng; Gao, Zhen; Li, Hui; Li, Qin; Zhang, Caixi; Xu, Wenping; Song, Shiren; Ma, Chao; Wang, Shiping

2018-03-13

Grapevine is among the fruit crops with high economic value, and because of the economic losses caused by abiotic stresses, the stress resistance of Vitis vinifera has become an increasingly important research area. Among the mechanisms responding to environmental stresses, the role of miRNA has received much attention recently. qRT-PCR is a powerful method for miRNA quantitation, but the accuracy of the method strongly depends on the appropriate reference genes. To determine the most suitable reference genes for grapevine miRNA qRT-PCR, 15 genes were chosen as candidate reference genes. After eliminating 6 candidate reference genes with unsatisfactory amplification efficiency, the expression stability of the remaining candidate reference genes under salinity, cold and drought was analysed using four algorithms, geNorm, NormFinder, deltaCt and Bestkeeper. The results indicated that U6 snRNA was the most suitable reference gene under salinity and cold stresses; whereas miR168 was the best for drought stress. The best reference gene sets for salinity, cold and drought stresses were miR160e + miR164a, miR160e + miR168 and ACT + UBQ + GAPDH, respectively. The selected reference genes or gene sets were verified using miR319 or miR408 as the target gene.

Selection and Validation of Reference Genes for qRT-PCR Expression Analysis of Candidate Genes Involved in Olfactory Communication in the Butterfly Bicyclus anynana

PubMed Central

Arun, Alok; Baumlé, Véronique; Amelot, Gaël; Nieberding, Caroline M.

2015-01-01

Real-time quantitative reverse transcription PCR (qRT-PCR) is a technique widely used to quantify the transcriptional expression level of candidate genes. qRT-PCR requires the selection of one or several suitable reference genes, whose expression profiles remain stable across conditions, to normalize the qRT-PCR expression profiles of candidate genes. Although several butterfly species (Lepidoptera) have become important models in molecular evolutionary ecology, so far no study aimed at identifying reference genes for accurate data normalization for any butterfly is available. The African bush brown butterfly Bicyclus anynana has drawn considerable attention owing to its suitability as a model for evolutionary ecology, and we here provide a maiden extensive study to identify suitable reference gene in this species. We monitored the expression profile of twelve reference genes: eEF-1α, FK506, UBQL40, RpS8, RpS18, HSP, GAPDH, VATPase, ACT3, TBP, eIF2 and G6PD. We tested the stability of their expression profiles in three different tissues (wings, brains, antennae), two developmental stages (pupal and adult) and two sexes (male and female), all of which were subjected to two food treatments (food stress and control feeding ad libitum). The expression stability and ranking of twelve reference genes was assessed using two algorithm-based methods, NormFinder and geNorm. Both methods identified RpS8 as the best suitable reference gene for expression data normalization. We also showed that the use of two reference genes is sufficient to effectively normalize the qRT-PCR data under varying tissues and experimental conditions that we used in B. anynana. Finally, we tested the effect of choosing reference genes with different stability on the normalization of the transcript abundance of a candidate gene involved in olfactory communication in B. anynana, the Fatty Acyl Reductase 2, and we confirmed that using an unstable reference gene can drastically alter the expression profile of the target candidate genes. PMID:25793735

Selection and validation of reference genes for qRT-PCR expression analysis of candidate genes involved in olfactory communication in the butterfly Bicyclus anynana.

PubMed

Arun, Alok; Baumlé, Véronique; Amelot, Gaël; Nieberding, Caroline M

2015-01-01

Real-time quantitative reverse transcription PCR (qRT-PCR) is a technique widely used to quantify the transcriptional expression level of candidate genes. qRT-PCR requires the selection of one or several suitable reference genes, whose expression profiles remain stable across conditions, to normalize the qRT-PCR expression profiles of candidate genes. Although several butterfly species (Lepidoptera) have become important models in molecular evolutionary ecology, so far no study aimed at identifying reference genes for accurate data normalization for any butterfly is available. The African bush brown butterfly Bicyclus anynana has drawn considerable attention owing to its suitability as a model for evolutionary ecology, and we here provide a maiden extensive study to identify suitable reference gene in this species. We monitored the expression profile of twelve reference genes: eEF-1α, FK506, UBQL40, RpS8, RpS18, HSP, GAPDH, VATPase, ACT3, TBP, eIF2 and G6PD. We tested the stability of their expression profiles in three different tissues (wings, brains, antennae), two developmental stages (pupal and adult) and two sexes (male and female), all of which were subjected to two food treatments (food stress and control feeding ad libitum). The expression stability and ranking of twelve reference genes was assessed using two algorithm-based methods, NormFinder and geNorm. Both methods identified RpS8 as the best suitable reference gene for expression data normalization. We also showed that the use of two reference genes is sufficient to effectively normalize the qRT-PCR data under varying tissues and experimental conditions that we used in B. anynana. Finally, we tested the effect of choosing reference genes with different stability on the normalization of the transcript abundance of a candidate gene involved in olfactory communication in B. anynana, the Fatty Acyl Reductase 2, and we confirmed that using an unstable reference gene can drastically alter the expression profile of the target candidate genes.

"Contrasting patterns of selection at Pinus pinaster Ait. Drought stress candidate genes as revealed by genetic differentiation analyses".

PubMed

Eveno, Emmanuelle; Collada, Carmen; Guevara, M Angeles; Léger, Valérie; Soto, Alvaro; Díaz, Luis; Léger, Patrick; González-Martínez, Santiago C; Cervera, M Teresa; Plomion, Christophe; Garnier-Géré, Pauline H

2008-02-01

The importance of natural selection for shaping adaptive trait differentiation among natural populations of allogamous tree species has long been recognized. Determining the molecular basis of local adaptation remains largely unresolved, and the respective roles of selection and demography in shaping population structure are actively debated. Using a multilocus scan that aims to detect outliers from simulated neutral expectations, we analyzed patterns of nucleotide diversity and genetic differentiation at 11 polymorphic candidate genes for drought stress tolerance in phenotypically contrasted Pinus pinaster Ait. populations across its geographical range. We compared 3 coalescent-based methods: 2 frequentist-like, including 1 approach specifically developed for biallelic single nucleotide polymorphisms (SNPs) here and 1 Bayesian. Five genes showed outlier patterns that were robust across methods at the haplotype level for 2 of them. Two genes presented higher F(ST) values than expected (PR-AGP4 and erd3), suggesting that they could have been affected by the action of diversifying selection among populations. In contrast, 3 genes presented lower F(ST) values than expected (dhn-1, dhn2, and lp3-1), which could represent signatures of homogenizing selection among populations. A smaller proportion of outliers were detected at the SNP level suggesting the potential functional significance of particular combinations of sites in drought-response candidate genes. The Bayesian method appeared robust to low sample sizes, flexible to assumptions regarding migration rates, and powerful for detecting selection at the haplotype level, but the frequentist-like method adapted to SNPs was more efficient for the identification of outlier SNPs showing low differentiation. Population-specific effects estimated in the Bayesian method also revealed populations with lower immigration rates, which could have led to favorable situations for local adaptation. Outlier patterns are discussed in relation to the different genes' putative involvement in drought tolerance responses, from published results in transcriptomics and association mapping in P. pinaster and other related species. These genes clearly constitute relevant candidates for future association studies in P. pinaster.

Dopaminergic, Serotonergic, and Oxytonergic Candidate Genes Associated with Infant Attachment Security and Disorganization? In Search of Main and Interaction Effects

ERIC Educational Resources Information Center

Luijk, Maartje P. C. M.; Roisman, Glenn I.; Haltigan, John D.; Tiemeier, Henning; Booth-LaForce, Cathryn; van IJzendoorn, Marinus H.; Belsky, Jay; Uitterlinden, Andre G.; Jaddoe, Vincent W. V.; Hofman, Albert; Verhulst, Frank C.; Tharner, Anne; Bakermans-Kranenburg, Marian J.

2011-01-01

Background and methods: In two birth cohort studies with genetic, sensitive parenting, and attachment data of more than 1,000 infants in total, we tested main and interaction effects of candidate genes involved in the dopamine, serotonin, and oxytocin systems ("DRD4", "DRD2", "COMT", "5-HTT", "OXTR") on attachment security and disorganization.…

Identification of genes from the Treacher Collins candidate region

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dixon, M.; Dixon, J.; Edwards, S.

Treacher Collins syndrome (TCOF1) is an autosomal dominant disorder of craniofacial development. The TCOF1 locus has previously been mapped to chromosome 5q32-33. The candidate gene region has been defined as being between two flanking markers, ribosomal protein S14 (RPS14) and Annexin 6 (ANX6), by analyzing recombination events in affected individuals. It is estimated that the distance between these flanking markers is 500 kb by three separate analysis methods: (1) radiation hybrid mapping; (2) genetic linkage; and (3) YAC contig analysis. A cosmid contig which spans the candidate gene region for TCOF1 has been constructed by screening the Los Alamos Nationalmore » Laboratory flow-sorted chromosome 5 cosmid library. Cosmids were obtained by using a combination of probes generated from YAC end clones, Alu-PCR fragments from YACs, and asymmetric PCR fragments from both T7 and T3 cosmid ends. Exon amplifications, the selection of genomic coding sequences based upon the presence of functional splice acceptor and donor sites, was used to identify potential exon sequences. Sequences found to be conserved between species were then used to screen cDNA libraries in order to identify candidate genes. To date, four different cDNAs have been isolated from this region and are being analyzed as potential candidate genes for TCOF1. These include the genes encoding plasma glutathione peroxidase (GPX3), heparin sulfate sulfotransferase (HSST), a gene with homology to the ETS family of proteins and one which shows no homology to any known genes. Work is also in progress to identify and characterize additional cDNAs from the candidate gene region.« less

Selection of Reference Genes for Expression Studies of Xenobiotic Adaptation in Tetranychus urticae.

PubMed

Morales, Mariany Ashanty; Mendoza, Bianca Marie; Lavine, Laura Corley; Lavine, Mark Daniel; Walsh, Douglas Bruce; Zhu, Fang

2016-01-01

Quantitative real-time PCR (qRT-PCR) is an extensively used, high-throughput method to analyze transcriptional expression of genes of interest. An appropriate normalization strategy with reliable reference genes is required for calculating gene expression across diverse experimental conditions. In this study, we aim to identify the most stable reference genes for expression studies of xenobiotic adaptation in Tetranychus urticae, an extremely polyphagous herbivore causing significant yield reduction of agriculture. We chose eight commonly used housekeeping genes as candidates. The qRT-PCR expression data for these genes were evaluated from seven populations: a susceptible and three acaricide resistant populations feeding on lima beans, and three other susceptible populations which had been shifted host from lima beans to three other plant species. The stability of the candidate reference genes was then assessed using four different algorithms (comparative ΔCt method, geNorm, NormFinder, and BestKeeper). Additionally, we used an online web-based tool (RefFinder) to assign an overall final rank for each candidate gene. Our study found that CycA and Rp49 are best for investigating gene expression in acaricide susceptible and resistant populations. GAPDH, Rp49, and Rpl18 are best for host plant shift studies. And GAPDH and Rp49 were the most stable reference genes when investigating gene expression under changes in both experimental conditions. These results will facilitate research in revealing molecular mechanisms underlying the xenobiotic adaptation of this notorious agricultural pest.

Selection of Reference Genes for Expression Studies of Xenobiotic Adaptation in Tetranychus urticae

PubMed Central

Morales, Mariany Ashanty; Mendoza, Bianca Marie; Lavine, Laura Corley; Lavine, Mark Daniel; Walsh, Douglas Bruce; Zhu, Fang

2016-01-01

Quantitative real-time PCR (qRT-PCR) is an extensively used, high-throughput method to analyze transcriptional expression of genes of interest. An appropriate normalization strategy with reliable reference genes is required for calculating gene expression across diverse experimental conditions. In this study, we aim to identify the most stable reference genes for expression studies of xenobiotic adaptation in Tetranychus urticae, an extremely polyphagous herbivore causing significant yield reduction of agriculture. We chose eight commonly used housekeeping genes as candidates. The qRT-PCR expression data for these genes were evaluated from seven populations: a susceptible and three acaricide resistant populations feeding on lima beans, and three other susceptible populations which had been shifted host from lima beans to three other plant species. The stability of the candidate reference genes was then assessed using four different algorithms (comparative ΔCt method, geNorm, NormFinder, and BestKeeper). Additionally, we used an online web-based tool (RefFinder) to assign an overall final rank for each candidate gene. Our study found that CycA and Rp49 are best for investigating gene expression in acaricide susceptible and resistant populations. GAPDH, Rp49, and Rpl18 are best for host plant shift studies. And GAPDH and Rp49 were the most stable reference genes when investigating gene expression under changes in both experimental conditions. These results will facilitate research in revealing molecular mechanisms underlying the xenobiotic adaptation of this notorious agricultural pest. PMID:27570487

Gene Prioritization of Resistant Rice Gene against Xanthomas oryzae pv. oryzae by Using Text Mining Technologies

PubMed Central

Xia, Jingbo; Zhang, Xing; Yuan, Daojun; Chen, Lingling; Webster, Jonathan; Fang, Alex Chengyu

2013-01-01

To effectively assess the possibility of the unknown rice protein resistant to Xanthomonas oryzae pv. oryzae, a hybrid strategy is proposed to enhance gene prioritization by combining text mining technologies with a sequence-based approach. The text mining technique of term frequency inverse document frequency is used to measure the importance of distinguished terms which reflect biomedical activity in rice before candidate genes are screened and vital terms are produced. Afterwards, a built-in classifier under the chaos games representation algorithm is used to sieve the best possible candidate gene. Our experiment results show that the combination of these two methods achieves enhanced gene prioritization. PMID:24371834

Gene prioritization of resistant rice gene against Xanthomas oryzae pv. oryzae by using text mining technologies.

PubMed

Xia, Jingbo; Zhang, Xing; Yuan, Daojun; Chen, Lingling; Webster, Jonathan; Fang, Alex Chengyu

2013-01-01

To effectively assess the possibility of the unknown rice protein resistant to Xanthomonas oryzae pv. oryzae, a hybrid strategy is proposed to enhance gene prioritization by combining text mining technologies with a sequence-based approach. The text mining technique of term frequency inverse document frequency is used to measure the importance of distinguished terms which reflect biomedical activity in rice before candidate genes are screened and vital terms are produced. Afterwards, a built-in classifier under the chaos games representation algorithm is used to sieve the best possible candidate gene. Our experiment results show that the combination of these two methods achieves enhanced gene prioritization.

Genome-Wide Specific Selection in Three Domestic Sheep Breeds.

PubMed

Wang, Huihua; Zhang, Li; Cao, Jiaxve; Wu, Mingming; Ma, Xiaomeng; Liu, Zhen; Liu, Ruizao; Zhao, Fuping; Wei, Caihong; Du, Lixin

2015-01-01

Commercial sheep raised for mutton grow faster than traditional Chinese sheep breeds. Here, we aimed to evaluate genetic selection among three different types of sheep breed: two well-known commercial mutton breeds and one indigenous Chinese breed. We first combined locus-specific branch lengths and di statistical methods to detect candidate regions targeted by selection in the three different populations. The results showed that the genetic distances reached at least medium divergence for each pairwise combination. We found these two methods were highly correlated, and identified many growth-related candidate genes undergoing artificial selection. For production traits, APOBR and FTO are associated with body mass index. For meat traits, ALDOA, STK32B and FAM190A are related to marbling. For reproduction traits, CCNB2 and SLC8A3 affect oocyte development. We also found two well-known genes, GHR (which affects meat production and quality) and EDAR (associated with hair thickness) were associated with German mutton merino sheep. Furthermore, four genes (POL, RPL7, MSL1 and SHISA9) were associated with pre-weaning gain in our previous genome-wide association study. Our results indicated that combine locus-specific branch lengths and di statistical approaches can reduce the searching ranges for specific selection. And we got many credible candidate genes which not only confirm the results of previous reports, but also provide a suite of novel candidate genes in defined breeds to guide hybridization breeding.

Mutational Landscape of Candidate Genes in Familial Prostate Cancer

PubMed Central

Johnson, Anna M.; Zuhlke, Kimberly A.; Plotts, Chris; McDonnell, Shannon K.; Middha, Sumit; Riska, Shaun M.; Thibodeau, Stephen N.; Douglas, Julie A.; Cooney, Kathleen A.

2014-01-01

Background Family history is a major risk factor for prostate cancer (PCa), suggesting a genetic component to the disease. However, traditional linkage and association studies have failed to fully elucidate the underlying genetic basis of familial PCa. Methods Here we use a candidate gene approach to identify potential PCa susceptibility variants in whole exome sequencing data from familial PCa cases. Six hundred ninety-seven candidate genes were identified based on function, location near a known chromosome 17 linkage signal, and/or previous association with prostate or other cancers. Single nucleotide variants (SNVs) in these candidate genes were identified in whole exome sequence data from 33 PCa cases from 11 multiplex PCa families (3 cases/family). Results Overall, 4856 candidate gene SNVs were identified, including 1052 missense and 10 nonsense variants. Twenty missense variants were shared by all 3 family members in each family in which they were observed. Additionally, 15 missense variants were shared by 2 of 3 family members and predicted to be deleterious by 5 different algorithms. Four missense variants, BLM Gln123Arg, PARP2 Arg283Gln, LRCC46 Ala295Thr and KIF2B Pro91Leu, and 1 nonsense variant, CYP3A43 Arg441Ter, showed complete co-segregation with PCa status. Twelve additional variants displayed partial co-segregation with PCa. Conclusions Forty-three nonsense and shared, missense variants were identified in our candidate genes. Further research is needed to determine the contribution of these variants to PCa susceptibility. PMID:25111073

Google Goes Cancer: Improving Outcome Prediction for Cancer Patients by Network-Based Ranking of Marker Genes

PubMed Central

Roy, Janine; Aust, Daniela; Knösel, Thomas; Rümmele, Petra; Jahnke, Beatrix; Hentrich, Vera; Rückert, Felix; Niedergethmann, Marco; Weichert, Wilko; Bahra, Marcus; Schlitt, Hans J.; Settmacher, Utz; Friess, Helmut; Büchler, Markus; Saeger, Hans-Detlev; Schroeder, Michael; Pilarsky, Christian; Grützmann, Robert

2012-01-01

Predicting the clinical outcome of cancer patients based on the expression of marker genes in their tumors has received increasing interest in the past decade. Accurate predictors of outcome and response to therapy could be used to personalize and thereby improve therapy. However, state of the art methods used so far often found marker genes with limited prediction accuracy, limited reproducibility, and unclear biological relevance. To address this problem, we developed a novel computational approach to identify genes prognostic for outcome that couples gene expression measurements from primary tumor samples with a network of known relationships between the genes. Our approach ranks genes according to their prognostic relevance using both expression and network information in a manner similar to Google's PageRank. We applied this method to gene expression profiles which we obtained from 30 patients with pancreatic cancer, and identified seven candidate marker genes prognostic for outcome. Compared to genes found with state of the art methods, such as Pearson correlation of gene expression with survival time, we improve the prediction accuracy by up to 7%. Accuracies were assessed using support vector machine classifiers and Monte Carlo cross-validation. We then validated the prognostic value of our seven candidate markers using immunohistochemistry on an independent set of 412 pancreatic cancer samples. Notably, signatures derived from our candidate markers were independently predictive of outcome and superior to established clinical prognostic factors such as grade, tumor size, and nodal status. As the amount of genomic data of individual tumors grows rapidly, our algorithm meets the need for powerful computational approaches that are key to exploit these data for personalized cancer therapies in clinical practice. PMID:22615549

Exploring Valid Reference Genes for Quantitative Real-time PCR Analysis in Plutella xylostella (Lepidoptera: Plutellidae)

PubMed Central

Fu, Wei; Xie, Wen; Zhang, Zhuo; Wang, Shaoli; Wu, Qingjun; Liu, Yong; Zhou, Xiaomao; Zhou, Xuguo; Zhang, Youjun

2013-01-01

Abstract: Quantitative real-time PCR (qRT-PCR), a primary tool in gene expression analysis, requires an appropriate normalization strategy to control for variation among samples. The best option is to compare the mRNA level of a target gene with that of reference gene(s) whose expression level is stable across various experimental conditions. In this study, expression profiles of eight candidate reference genes from the diamondback moth, Plutella xylostella, were evaluated under diverse experimental conditions. RefFinder, a web-based analysis tool, integrates four major computational programs including geNorm, Normfinder, BestKeeper, and the comparative ΔCt method to comprehensively rank the tested candidate genes. Elongation factor 1 (EF1) was the most suited reference gene for the biotic factors (development stage, tissue, and strain). In contrast, although appropriate reference gene(s) do exist for several abiotic factors (temperature, photoperiod, insecticide, and mechanical injury), we were not able to identify a single universal reference gene. Nevertheless, a suite of candidate reference genes were specifically recommended for selected experimental conditions. Our finding is the first step toward establishing a standardized qRT-PCR analysis of this agriculturally important insect pest. PMID:23983612

Transcriptomic biomarkers of altered erythropoiesis to detect autologous blood transfusion.

PubMed

Salamin, Olivier; Mignot, Jonathan; Kuuranne, Tiia; Saugy, Martial; Leuenberger, Nicolas

2018-03-01

Autologous blood transfusion is a powerful means of improving performance and remains one of the most challenging methods to detect. Recent investigations have identified 3 candidate reticulocytes genes whose expression was significantly influenced by blood transfusion. Using quantitative reverse transcription polymerase chain reaction as an alternative quantitative method, the present study supports that delta-aminolevulinate synthase 2 (ALAS2), carbonic anhydrase (CA1), and solute carrier family 4 member 1 (SLC4A1) genes are down-regulated post-transfusion. The expression of these genes exhibited stronger correlation with immature reticulocyte fraction than with reticulocytes percentage. Moreover, the repression of reticulocytes' gene expression was more pronounced than the diminution of immature reticulocyte fraction and reticulocyte percentage following blood transfusion. It suggests that the 3 candidate genes are reliable predictors of bone marrow's response to blood transfusion and that they represent potential biomarkers for the detection of this method prohibited in sports. Copyright © 2017 John Wiley & Sons, Ltd.

Effects of DGAT1 gene on meat and carcass fatness quality in Chinese commercial cattle.

PubMed

Yuan, Zhengrong; Li, Junya; Li, Jiao; Gao, Xue; Gao, Huijiang; Xu, Shangzhong

2013-02-01

This study was designed to investigate the candidate single nucleotide polymorphisms (SNPs) in the exon's region of bovine diacylglycerol O-acyltransferase (DGAT1) gene using bioinformatics and experimental methods. A total of 17 SNPs were screened from public data resources and DNA sequencing. Three SNPs (c.572A>G, c.1241C>T and c.1416T>G) of these candidate SNPs were genotyped by created restriction site-polymerase chain reaction (CRS-PCR) methods. The gene-specific SNP markers and their effects on meat and carcass fatness quality traits were evaluated in Chinese commercial cattle. The c.572A>G and c.1416T>G significantly effected on backfat thickness, longissimus muscle area, marbling score, fat color and Warner-Bratzler shear force. No significant association was detected between the c.1241C>T and measured traits. Results from this study suggested that the SNP markers may be effective for the marker-assisted selection of meat and carcass fatness quality traits, and added new evidence that DGAT1 gene is an important candidate gene for the improvement of meat and carcass fatness quality in beef cattle industry.

Identification of genes related to proliferative diabetic retinopathy through RWR algorithm based on protein-protein interaction network.

PubMed

Zhang, Jian; Suo, Yan; Liu, Min; Xu, Xun

2018-06-01

Proliferative diabetic retinopathy (PDR) is one of the most common complications of diabetes and can lead to blindness. Proteomic studies have provided insight into the pathogenesis of PDR and a series of PDR-related genes has been identified but are far from fully characterized because the experimental methods are expensive and time consuming. In our previous study, we successfully identified 35 candidate PDR-related genes through the shortest-path algorithm. In the current study, we developed a computational method using the random walk with restart (RWR) algorithm and the protein-protein interaction (PPI) network to identify potential PDR-related genes. After some possible genes were obtained by the RWR algorithm, a three-stage filtration strategy, which includes the permutation test, interaction test and enrichment test, was applied to exclude potential false positives caused by the structure of PPI network, the poor interaction strength, and the limited similarity on gene ontology (GO) terms and biological pathways. As a result, 36 candidate genes were discovered by the method which was different from the 35 genes reported in our previous study. A literature review showed that 21 of these 36 genes are supported by previous experiments. These findings suggest the robustness and complementary effects of both our efforts using different computational methods, thus providing an alternative method to study PDR pathogenesis. Copyright © 2017 Elsevier B.V. All rights reserved.

Cancer diagnosis marker extraction for soft tissue sarcomas based on gene expression profiling data by using projective adaptive resonance theory (PART) filtering method

PubMed Central

Takahashi, Hiro; Nemoto, Takeshi; Yoshida, Teruhiko; Honda, Hiroyuki; Hasegawa, Tadashi

2006-01-01

Background Recent advances in genome technologies have provided an excellent opportunity to determine the complete biological characteristics of neoplastic tissues, resulting in improved diagnosis and selection of treatment. To accomplish this objective, it is important to establish a sophisticated algorithm that can deal with large quantities of data such as gene expression profiles obtained by DNA microarray analysis. Results Previously, we developed the projective adaptive resonance theory (PART) filtering method as a gene filtering method. This is one of the clustering methods that can select specific genes for each subtype. In this study, we applied the PART filtering method to analyze microarray data that were obtained from soft tissue sarcoma (STS) patients for the extraction of subtype-specific genes. The performance of the filtering method was evaluated by comparison with other widely used methods, such as signal-to-noise, significance analysis of microarrays, and nearest shrunken centroids. In addition, various combinations of filtering and modeling methods were used to extract essential subtype-specific genes. The combination of the PART filtering method and boosting – the PART-BFCS method – showed the highest accuracy. Seven genes among the 15 genes that are frequently selected by this method – MIF, CYFIP2, HSPCB, TIMP3, LDHA, ABR, and RGS3 – are known prognostic marker genes for other tumors. These genes are candidate marker genes for the diagnosis of STS. Correlation analysis was performed to extract marker genes that were not selected by PART-BFCS. Sixteen genes among those extracted are also known prognostic marker genes for other tumors, and they could be candidate marker genes for the diagnosis of STS. Conclusion The procedure that consisted of two steps, such as the PART-BFCS and the correlation analysis, was proposed. The results suggest that novel diagnostic and therapeutic targets for STS can be extracted by a procedure that includes the PART filtering method. PMID:16948864

A Novel Strategy for Selection and Validation of Reference Genes in Dynamic Multidimensional Experimental Design in Yeast

PubMed Central

Cankorur-Cetinkaya, Ayca; Dereli, Elif; Eraslan, Serpil; Karabekmez, Erkan; Dikicioglu, Duygu; Kirdar, Betul

2012-01-01

Background Understanding the dynamic mechanism behind the transcriptional organization of genes in response to varying environmental conditions requires time-dependent data. The dynamic transcriptional response obtained by real-time RT-qPCR experiments could only be correctly interpreted if suitable reference genes are used in the analysis. The lack of available studies on the identification of candidate reference genes in dynamic gene expression studies necessitates the identification and the verification of a suitable gene set for the analysis of transient gene expression response. Principal Findings In this study, a candidate reference gene set for RT-qPCR analysis of dynamic transcriptional changes in Saccharomyces cerevisiae was determined using 31 different publicly available time series transcriptome datasets. Ten of the twelve candidates (TPI1, FBA1, CCW12, CDC19, ADH1, PGK1, GCN4, PDC1, RPS26A and ARF1) we identified were not previously reported as potential reference genes. Our method also identified the commonly used reference genes ACT1 and TDH3. The most stable reference genes from this pool were determined as TPI1, FBA1, CDC19 and ACT1 in response to a perturbation in the amount of available glucose and as FBA1, TDH3, CCW12 and ACT1 in response to a perturbation in the amount of available ammonium. The use of these newly proposed gene sets outperformed the use of common reference genes in the determination of dynamic transcriptional response of the target genes, HAP4 and MEP2, in response to relaxation from glucose and ammonium limitations, respectively. Conclusions A candidate reference gene set to be used in dynamic real-time RT-qPCR expression profiling in yeast was proposed for the first time in the present study. Suitable pools of stable reference genes to be used under different experimental conditions could be selected from this candidate set in order to successfully determine the expression profiles for the genes of interest. PMID:22675547

Detecting novel genes with sparse arrays

PubMed Central

Haiminen, Niina; Smit, Bart; Rautio, Jari; Vitikainen, Marika; Wiebe, Marilyn; Martinez, Diego; Chee, Christine; Kunkel, Joe; Sanchez, Charles; Nelson, Mary Anne; Pakula, Tiina; Saloheimo, Markku; Penttilä, Merja; Kivioja, Teemu

2014-01-01

Species-specific genes play an important role in defining the phenotype of an organism. However, current gene prediction methods can only efficiently find genes that share features such as sequence similarity or general sequence characteristics with previously known genes. Novel sequencing methods and tiling arrays can be used to find genes without prior information and they have demonstrated that novel genes can still be found from extensively studied model organisms. Unfortunately, these methods are expensive and thus are not easily applicable, e.g., to finding genes that are expressed only in very specific conditions. We demonstrate a method for finding novel genes with sparse arrays, applying it on the 33.9 Mb genome of the filamentous fungus Trichoderma reesei. Our computational method does not require normalisations between arrays and it takes into account the multiple-testing problem typical for analysis of microarray data. In contrast to tiling arrays, that use overlapping probes, only one 25mer microarray oligonucleotide probe was used for every 100 b. Thus, only relatively little space on a microarray slide was required to cover the intergenic regions of a genome. The analysis was done as a by-product of a conventional microarray experiment with no additional costs. We found at least 23 good candidates for novel transcripts that could code for proteins and all of which were expressed at high levels. Candidate genes were found to neighbour ire1 and cre1 and many other regulatory genes. Our simple, low-cost method can easily be applied to finding novel species-specific genes without prior knowledge of their sequence properties. PMID:20691772

Candidate genes for obesity-susceptibility show enriched association within a large genome-wide association study for BMI.

PubMed

Vimaleswaran, Karani S; Tachmazidou, Ioanna; Zhao, Jing Hua; Hirschhorn, Joel N; Dudbridge, Frank; Loos, Ruth J F

2012-10-15

Before the advent of genome-wide association studies (GWASs), hundreds of candidate genes for obesity-susceptibility had been identified through a variety of approaches. We examined whether those obesity candidate genes are enriched for associations with body mass index (BMI) compared with non-candidate genes by using data from a large-scale GWAS. A thorough literature search identified 547 candidate genes for obesity-susceptibility based on evidence from animal studies, Mendelian syndromes, linkage studies, genetic association studies and expression studies. Genomic regions were defined to include the genes ±10 kb of flanking sequence around candidate and non-candidate genes. We used summary statistics publicly available from the discovery stage of the genome-wide meta-analysis for BMI performed by the genetic investigation of anthropometric traits consortium in 123 564 individuals. Hypergeometric, rank tail-strength and gene-set enrichment analysis tests were used to test for the enrichment of association in candidate compared with non-candidate genes. The hypergeometric test of enrichment was not significant at the 5% P-value quantile (P = 0.35), but was nominally significant at the 25% quantile (P = 0.015). The rank tail-strength and gene-set enrichment tests were nominally significant for the full set of genes and borderline significant for the subset without SNPs at P < 10(-7). Taken together, the observed evidence for enrichment suggests that the candidate gene approach retains some value. However, the degree of enrichment is small despite the extensive number of candidate genes and the large sample size. Studies that focus on candidate genes have only slightly increased chances of detecting associations, and are likely to miss many true effects in non-candidate genes, at least for obesity-related traits.

Utilizing Gene Tree Variation to Identify Candidate Effector Genes in Zymoseptoria tritici

PubMed Central

McDonald, Megan C.; McGinness, Lachlan; Hane, James K.; Williams, Angela H.; Milgate, Andrew; Solomon, Peter S.

2016-01-01

Zymoseptoria tritici is a host-specific, necrotrophic pathogen of wheat. Infection by Z. tritici is characterized by its extended latent period, which typically lasts 2 wks, and is followed by extensive host cell death, and rapid proliferation of fungal biomass. This work characterizes the level of genomic variation in 13 isolates, for which we have measured virulence on 11 wheat cultivars with differential resistance genes. Between the reference isolate, IPO323, and the 13 Australian isolates we identified over 800,000 single nucleotide polymorphisms, of which ∼10% had an effect on the coding regions of the genome. Furthermore, we identified over 1700 probable presence/absence polymorphisms in genes across the Australian isolates using de novo assembly. Finally, we developed a gene tree sorting method that quickly identifies groups of isolates within a single gene alignment whose sequence haplotypes correspond with virulence scores on a single wheat cultivar. Using this method, we have identified < 100 candidate effector genes whose gene sequence correlates with virulence toward a wheat cultivar carrying a major resistance gene. PMID:26837952

The Genetic Basis for Variation in Sensitivity to Lead Toxicity in Drosophila melanogaster

PubMed Central

Zhou, Shanshan; Morozova, Tatiana V.; Hussain, Yasmeen N.; Luoma, Sarah E.; McCoy, Lenovia; Yamamoto, Akihiko; Mackay, Trudy F.C.; Anholt, Robert R.H.

2016-01-01

Background: Lead toxicity presents a worldwide health problem, especially due to its adverse effects on cognitive development in children. However, identifying genes that give rise to individual variation in susceptibility to lead toxicity is challenging in human populations. Objectives: Our goal was to use Drosophila melanogaster to identify evolutionarily conserved candidate genes associated with individual variation in susceptibility to lead exposure. Methods: To identify candidate genes associated with variation in susceptibility to lead toxicity, we measured effects of lead exposure on development time, viability and adult activity in the Drosophila melanogaster Genetic Reference Panel (DGRP) and performed genome-wide association analyses to identify candidate genes. We used mutants to assess functional causality of candidate genes and constructed a genetic network associated with variation in sensitivity to lead exposure, on which we could superimpose human orthologs. Results: We found substantial heritabilities for all three traits and identified candidate genes associated with variation in susceptibility to lead exposure for each phenotype. The genetic architectures that determine variation in sensitivity to lead exposure are highly polygenic. Gene ontology and network analyses showed enrichment of genes associated with early development and function of the nervous system. Conclusions: Drosophila melanogaster presents an advantageous model to study the genetic underpinnings of variation in susceptibility to lead toxicity. Evolutionary conservation of cellular pathways that respond to toxic exposure allows predictions regarding orthologous genes and pathways across phyla. Thus, studies in the D. melanogaster model system can identify candidate susceptibility genes to guide subsequent studies in human populations. Citation: Zhou S, Morozova TV, Hussain YN, Luoma SE, McCoy L, Yamamoto A, Mackay TF, Anholt RR. 2016. The genetic basis for variation in sensitivity to lead toxicity in Drosophila melanogaster. Environ Health Perspect 124:1062–1070; http://dx.doi.org/10.1289/ehp.1510513 PMID:26859824

Indel-seq: a fast-forward genetics approach for identification of trait-associated putative candidate genomic regions and its application in pigeonpea (Cajanus cajan).

PubMed

Singh, Vikas K; Khan, Aamir W; Saxena, Rachit K; Sinha, Pallavi; Kale, Sandip M; Parupalli, Swathi; Kumar, Vinay; Chitikineni, Annapurna; Vechalapu, Suryanarayana; Sameer Kumar, Chanda Venkata; Sharma, Mamta; Ghanta, Anuradha; Yamini, Kalinati Narasimhan; Muniswamy, Sonnappa; Varshney, Rajeev K

2017-07-01

Identification of candidate genomic regions associated with target traits using conventional mapping methods is challenging and time-consuming. In recent years, a number of single nucleotide polymorphism (SNP)-based mapping approaches have been developed and used for identification of candidate/putative genomic regions. However, in the majority of these studies, insertion-deletion (Indel) were largely ignored. For efficient use of Indels in mapping target traits, we propose Indel-seq approach, which is a combination of whole-genome resequencing (WGRS) and bulked segregant analysis (BSA) and relies on the Indel frequencies in extreme bulks. Deployment of Indel-seq approach for identification of candidate genomic regions associated with fusarium wilt (FW) and sterility mosaic disease (SMD) resistance in pigeonpea has identified 16 Indels affecting 26 putative candidate genes. Of these 26 affected putative candidate genes, 24 genes showed effect in the upstream/downstream of the genic region and two genes showed effect in the genes. Validation of these 16 candidate Indels in other FW- and SMD-resistant and FW- and SMD-susceptible genotypes revealed a significant association of five Indels (three for FW and two for SMD resistance). Comparative analysis of Indel-seq with other genetic mapping approaches highlighted the importance of the approach in identification of significant genomic regions associated with target traits. Therefore, the Indel-seq approach can be used for quick and precise identification of candidate genomic regions for any target traits in any crop species. © 2016 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

Novel candidate genes may be possible predisposing factors revealed by whole exome sequencing in familial esophageal squamous cell carcinoma.

PubMed

Forouzanfar, Narjes; Baranova, Ancha; Milanizadeh, Saman; Heravi-Moussavi, Alireza; Jebelli, Amir; Abbaszadegan, Mohammad Reza

2017-05-01

Esophageal squamous cell carcinoma is one of the deadliest of all the cancers. Its metastatic properties portend poor prognosis and high rate of recurrence. A more advanced method to identify new molecular biomarkers predicting disease prognosis can be whole exome sequencing. Here, we report the most effective genetic variants of the Notch signaling pathway in esophageal squamous cell carcinoma susceptibility by whole exome sequencing. We analyzed nine probands in unrelated familial esophageal squamous cell carcinoma pedigrees to identify candidate genes. Genomic DNA was extracted and whole exome sequencing performed to generate information about genetic variants in the coding regions. Bioinformatics software applications were utilized to exploit statistical algorithms to demonstrate protein structure and variants conservation. Polymorphic regions were excluded by false-positive investigations. Gene-gene interactions were analyzed for Notch signaling pathway candidates. We identified novel and damaging variants of the Notch signaling pathway through extensive pathway-oriented filtering and functional predictions, which led to the study of 27 candidate novel mutations in all nine patients. Detection of the trinucleotide repeat containing 6B gene mutation (a slice site alteration) in five of the nine probands, but not in any of the healthy samples, suggested that it may be a susceptibility factor for familial esophageal squamous cell carcinoma. Noticeably, 8 of 27 novel candidate gene mutations (e.g. epidermal growth factor, signal transducer and activator of transcription 3, MET) act in a cascade leading to cell survival and proliferation. Our results suggest that the trinucleotide repeat containing 6B mutation may be a candidate predisposing gene in esophageal squamous cell carcinoma. In addition, some of the Notch signaling pathway genetic mutations may act as key contributors to esophageal squamous cell carcinoma.

The Effects of Selenium Supplementation on Gene Expression Related to Insulin and Lipid in Infertile Polycystic Ovary Syndrome Women Candidate for In Vitro Fertilization: a Randomized, Double-Blind, Placebo-Controlled Trial.

PubMed

Zadeh Modarres, Shahrzad; Heidar, Zahra; Foroozanfard, Fatemeh; Rahmati, Zahra; Aghadavod, Esmat; Asemi, Zatollah

2018-06-01

This study was conducted to evaluate the effects of selenium supplementation on gene expression related to insulin and lipid in infertile women with polycystic ovary syndrome (PCOS) candidate for in vitro fertilization (IVF). This randomized double-blind, placebo-controlled trial was conducted among 40 infertile women with PCOS candidate for IVF. Subjects were randomly allocated into two groups to intake either 200-μg selenium (n = 20) or placebo (n = 20) per day for 8 weeks. Gene expression levels related to insulin and lipid were quantified in lymphocytes of women with PCOS candidate for IVF with RT-PCR method. Results of RT-PCR demonstrated that after the 8-week intervention, compared with the placebo, selenium supplementation upregulated gene expression of peroxisome proliferator-activated receptor gamma (PPAR-γ) (1.06 ± 0.15-fold increase vs. 0.94 ± 0.18-fold reduction, P = 0.02) and glucose transporter 1 (GLUT-1) (1.07 ± 0.20-fold increase vs. 0.87 ± 0.18-fold reduction, P = 0.003) in lymphocytes of women with PCOS candidate for IVF. In addition, compared with the placebo, selenium supplementation downregulated gene expression of low-density lipoprotein receptor (LDLR) (0.88 ± 0.17-fold reduction vs. 1.05 ± 0.22-fold increase, P = 0.01) in lymphocytes of women with PCOS candidate for IVF. We did not observe any significant effect of selenium supplementation on gene expression levels of lipoprotein(a) [LP(a)] in lymphocytes of women with PCOS candidate for IVF. Overall, selenium supplementation for 8 weeks in lymphocytes of women with infertile PCOS candidate for IVF significantly increased gene expression levels of PPAR-γ and GLUT-1 and significantly decreased gene expression levels of LDLR, but did not affect LP(a). http://www.irct.ir : IRCT201704245623N113.

Genome-wide detection of selection signatures in Chinese indigenous Laiwu pigs revealed candidate genes regulating fat deposition in muscle.

PubMed

Chen, Minhui; Wang, Jiying; Wang, Yanping; Wu, Ying; Fu, Jinluan; Liu, Jian-Feng

2018-05-18

Currently, genome-wide scans for positive selection signatures in commercial breed have been investigated. However, few studies have focused on selection footprints of indigenous breeds. Laiwu pig is an invaluable Chinese indigenous pig breed with extremely high proportion of intramuscular fat (IMF), and an excellent model to detect footprint as the result of natural and artificial selection for fat deposition in muscle. In this study, based on GeneSeek Genomic profiler Porcine HD data, three complementary methods, F ST , iHS (integrated haplotype homozygosity score) and CLR (composite likelihood ratio), were implemented to detect selection signatures in the whole genome of Laiwu pigs. Totally, 175 candidate selected regions were obtained by at least two of the three methods, which covered 43.75 Mb genomic regions and corresponded to 1.79% of the genome sequence. Gene annotation of the selected regions revealed a list of functionally important genes for feed intake and fat deposition, reproduction, and immune response. Especially, in accordance to the phenotypic features of Laiwu pigs, among the candidate genes, we identified several genes, NPY1R, NPY5R, PIK3R1 and JAKMIP1, involved in the actions of two sets of neurons, which are central regulators in maintaining the balance between food intake and energy expenditure. Our results identified a number of regions showing signatures of selection, as well as a list of functionally candidate genes with potential effect on phenotypic traits, especially fat deposition in muscle. Our findings provide insights into the mechanisms of artificial selection of fat deposition and further facilitate follow-up functional studies.

Exome Sequencing and Linkage Analysis Identified Novel Candidate Genes in Recessive Intellectual Disability Associated with Ataxia.

PubMed

Jazayeri, Roshanak; Hu, Hao; Fattahi, Zohreh; Musante, Luciana; Abedini, Seyedeh Sedigheh; Hosseini, Masoumeh; Wienker, Thomas F; Ropers, Hans Hilger; Najmabadi, Hossein; Kahrizi, Kimia

2015-10-01

Intellectual disability (ID) is a neuro-developmental disorder which causes considerable socio-economic problems. Some ID individuals are also affected by ataxia, and the condition includes different mutations affecting several genes. We used whole exome sequencing (WES) in combination with homozygosity mapping (HM) to identify the genetic defects in five consanguineous families among our cohort study, with two affected children with ID and ataxia as major clinical symptoms. We identified three novel candidate genes, RIPPLY1, MRPL10, SNX14, and a new mutation in known gene SURF1. All are autosomal genes, except RIPPLY1, which is located on the X chromosome. Two are housekeeping genes, implicated in transcription and translation regulation and intracellular trafficking, and two encode mitochondrial proteins. The pathogenesis of these variants was evaluated by mutation classification, bioinformatic methods, review of medical and biological relevance, co-segregation studies in the particular family, and a normal population study. Linkage analysis and exome sequencing of a small number of affected family members is a powerful new technique which can be used to decrease the number of candidate genes in heterogenic disorders such as ID, and may even identify the responsible gene(s).

Identifying metabolic enzymes with multiple types of association evidence

PubMed Central

Kharchenko, Peter; Chen, Lifeng; Freund, Yoav; Vitkup, Dennis; Church, George M

2006-01-01

Background Existing large-scale metabolic models of sequenced organisms commonly include enzymatic functions which can not be attributed to any gene in that organism. Existing computational strategies for identifying such missing genes rely primarily on sequence homology to known enzyme-encoding genes. Results We present a novel method for identifying genes encoding for a specific metabolic function based on a local structure of metabolic network and multiple types of functional association evidence, including clustering of genes on the chromosome, similarity of phylogenetic profiles, gene expression, protein fusion events and others. Using E. coli and S. cerevisiae metabolic networks, we illustrate predictive ability of each individual type of association evidence and show that significantly better predictions can be obtained based on the combination of all data. In this way our method is able to predict 60% of enzyme-encoding genes of E. coli metabolism within the top 10 (out of 3551) candidates for their enzymatic function, and as a top candidate within 43% of the cases. Conclusion We illustrate that a combination of genome context and other functional association evidence is effective in predicting genes encoding metabolic enzymes. Our approach does not rely on direct sequence homology to known enzyme-encoding genes, and can be used in conjunction with traditional homology-based metabolic reconstruction methods. The method can also be used to target orphan metabolic activities. PMID:16571130

LNDriver: identifying driver genes by integrating mutation and expression data based on gene-gene interaction network.

PubMed

Wei, Pi-Jing; Zhang, Di; Xia, Junfeng; Zheng, Chun-Hou

2016-12-23

Cancer is a complex disease which is characterized by the accumulation of genetic alterations during the patient's lifetime. With the development of the next-generation sequencing technology, multiple omics data, such as cancer genomic, epigenomic and transcriptomic data etc., can be measured from each individual. Correspondingly, one of the key challenges is to pinpoint functional driver mutations or pathways, which contributes to tumorigenesis, from millions of functional neutral passenger mutations. In this paper, in order to identify driver genes effectively, we applied a generalized additive model to mutation profiles to filter genes with long length and constructed a new gene-gene interaction network. Then we integrated the mutation data and expression data into the gene-gene interaction network. Lastly, greedy algorithm was used to prioritize candidate driver genes from the integrated data. We named the proposed method Length-Net-Driver (LNDriver). Experiments on three TCGA datasets, i.e., head and neck squamous cell carcinoma, kidney renal clear cell carcinoma and thyroid carcinoma, demonstrated that the proposed method was effective. Also, it can identify not only frequently mutated drivers, but also rare candidate driver genes.

Prioritizing chronic obstructive pulmonary disease (COPD) candidate genes in COPD-related networks

PubMed Central

Zhang, Yihua; Li, Wan; Feng, Yuyan; Guo, Shanshan; Zhao, Xilei; Wang, Yahui; He, Yuehan; He, Weiming; Chen, Lina

2017-01-01

Chronic obstructive pulmonary disease (COPD) is a multi-factor disease, which could be caused by many factors, including disturbances of metabolism and protein-protein interactions (PPIs). In this paper, a weighted COPD-related metabolic network and a weighted COPD-related PPI network were constructed base on COPD disease genes and functional information. Candidate genes in these weighted COPD-related networks were prioritized by making use of a gene prioritization method, respectively. Literature review and functional enrichment analysis of the top 100 genes in these two networks suggested the correlation of COPD and these genes. The performance of our gene prioritization method was superior to that of ToppGene and ToppNet for genes from the COPD-related metabolic network or the COPD-related PPI network after assessing using leave-one-out cross-validation, literature validation and functional enrichment analysis. The top-ranked genes prioritized from COPD-related metabolic and PPI networks could promote the better understanding about the molecular mechanism of this disease from different perspectives. The top 100 genes in COPD-related metabolic network or COPD-related PPI network might be potential markers for the diagnosis and treatment of COPD. PMID:29262568

Prioritizing chronic obstructive pulmonary disease (COPD) candidate genes in COPD-related networks.

PubMed

Zhang, Yihua; Li, Wan; Feng, Yuyan; Guo, Shanshan; Zhao, Xilei; Wang, Yahui; He, Yuehan; He, Weiming; Chen, Lina

2017-11-28

Chronic obstructive pulmonary disease (COPD) is a multi-factor disease, which could be caused by many factors, including disturbances of metabolism and protein-protein interactions (PPIs). In this paper, a weighted COPD-related metabolic network and a weighted COPD-related PPI network were constructed base on COPD disease genes and functional information. Candidate genes in these weighted COPD-related networks were prioritized by making use of a gene prioritization method, respectively. Literature review and functional enrichment analysis of the top 100 genes in these two networks suggested the correlation of COPD and these genes. The performance of our gene prioritization method was superior to that of ToppGene and ToppNet for genes from the COPD-related metabolic network or the COPD-related PPI network after assessing using leave-one-out cross-validation, literature validation and functional enrichment analysis. The top-ranked genes prioritized from COPD-related metabolic and PPI networks could promote the better understanding about the molecular mechanism of this disease from different perspectives. The top 100 genes in COPD-related metabolic network or COPD-related PPI network might be potential markers for the diagnosis and treatment of COPD.

Identification of novel candidate drivers connecting different dysfunctional levels for lung adenocarcinoma using protein-protein interactions and a shortest path approach

NASA Astrophysics Data System (ADS)

Chen, Lei; Huang, Tao; Zhang, Yu-Hang; Jiang, Yang; Zheng, Mingyue; Cai, Yu-Dong

2016-07-01

Tumors are formed by the abnormal proliferation of somatic cells with disordered growth regulation under the influence of tumorigenic factors. Recently, the theory of “cancer drivers” connects tumor initiation with several specific mutations in the so-called cancer driver genes. According to the differentiation of four basic levels between tumor and adjacent normal tissues, the cancer drivers can be divided into the following: (1) Methylation level, (2) microRNA level, (3) mutation level, and (4) mRNA level. In this study, a computational method is proposed to identify novel lung adenocarcinoma drivers based on dysfunctional genes on the methylation, microRNA, mutation and mRNA levels. First, a large network was constructed using protein-protein interactions. Next, we searched all of the shortest paths connecting dysfunctional genes on different levels and extracted new candidate genes lying on these paths. Finally, the obtained candidate genes were filtered by a permutation test and an additional strict selection procedure involving a betweenness ratio and an interaction score. Several candidate genes remained, which are deemed to be related to two different levels of cancer. The analyses confirmed our assertions that some have the potential to contribute to the tumorigenesis process on multiple levels.

MorphDB: Prioritizing Genes for Specialized Metabolism Pathways and Gene Ontology Categories in Plants.

PubMed

Zwaenepoel, Arthur; Diels, Tim; Amar, David; Van Parys, Thomas; Shamir, Ron; Van de Peer, Yves; Tzfadia, Oren

2018-01-01

Recent times have seen an enormous growth of "omics" data, of which high-throughput gene expression data are arguably the most important from a functional perspective. Despite huge improvements in computational techniques for the functional classification of gene sequences, common similarity-based methods often fall short of providing full and reliable functional information. Recently, the combination of comparative genomics with approaches in functional genomics has received considerable interest for gene function analysis, leveraging both gene expression based guilt-by-association methods and annotation efforts in closely related model organisms. Besides the identification of missing genes in pathways, these methods also typically enable the discovery of biological regulators (i.e., transcription factors or signaling genes). A previously built guilt-by-association method is MORPH, which was proven to be an efficient algorithm that performs particularly well in identifying and prioritizing missing genes in plant metabolic pathways. Here, we present MorphDB, a resource where MORPH-based candidate genes for large-scale functional annotations (Gene Ontology, MapMan bins) are integrated across multiple plant species. Besides a gene centric query utility, we present a comparative network approach that enables researchers to efficiently browse MORPH predictions across functional gene sets and species, facilitating efficient gene discovery and candidate gene prioritization. MorphDB is available at http://bioinformatics.psb.ugent.be/webtools/morphdb/morphDB/index/. We also provide a toolkit, named "MORPH bulk" (https://github.com/arzwa/morph-bulk), for running MORPH in bulk mode on novel data sets, enabling researchers to apply MORPH to their own species of interest.

SomInaClust: detection of cancer genes based on somatic mutation patterns of inactivation and clustering.

PubMed

Van den Eynden, Jimmy; Fierro, Ana Carolina; Verbeke, Lieven P C; Marchal, Kathleen

2015-04-23

With the advances in high throughput technologies, increasing amounts of cancer somatic mutation data are being generated and made available. Only a small number of (driver) mutations occur in driver genes and are responsible for carcinogenesis, while the majority of (passenger) mutations do not influence tumour biology. In this study, SomInaClust is introduced, a method that accurately identifies driver genes based on their mutation pattern across tumour samples and then classifies them into oncogenes or tumour suppressor genes respectively. SomInaClust starts from the observation that oncogenes mainly contain mutations that, due to positive selection, cluster at similar positions in a gene across patient samples, whereas tumour suppressor genes contain a high number of protein-truncating mutations throughout the entire gene length. The method was shown to prioritize driver genes in 9 different solid cancers. Furthermore it was found to be complementary to existing similar-purpose methods with the additional advantages that it has a higher sensitivity, also for rare mutations (occurring in less than 1% of all samples), and it accurately classifies candidate driver genes in putative oncogenes and tumour suppressor genes. Pathway enrichment analysis showed that the identified genes belong to known cancer signalling pathways, and that the distinction between oncogenes and tumour suppressor genes is biologically relevant. SomInaClust was shown to detect candidate driver genes based on somatic mutation patterns of inactivation and clustering and to distinguish oncogenes from tumour suppressor genes. The method could be used for the identification of new cancer genes or to filter mutation data for further data-integration purposes.

A whole genome SNP genotyping by DNA microarray and candidate gene association study for kidney stone disease

PubMed Central

2014-01-01

Background Kidney stone disease (KSD) is a complex disorder with unknown etiology in majority of the patients. Genetic and environmental factors may cause the disease. In the present study, we used DNA microarray to genotype single nucleotide polymorphisms (SNP) and performed candidate gene association analysis to determine genetic variations associated with the disease. Methods A whole genome SNP genotyping by DNA microarray was initially conducted in 101 patients and 105 control subjects. A set of 104 candidate genes reported to be involved in KSD, gathered from public databases and candidate gene association study databases, were evaluated for their variations associated with KSD. Results Altogether 82 SNPs distributed within 22 candidate gene regions showed significant differences in SNP allele frequencies between the patient and control groups (P < 0.05). Of these, 4 genes including BGLAP, AHSG, CD44, and HAO1, encoding osteocalcin, fetuin-A, CD44-molecule and glycolate oxidase 1, respectively, were further assessed for their associations with the disease because they carried high proportion of SNPs with statistical differences of allele frequencies between the patient and control groups within the gene. The total of 26 SNPs showed significant differences of allele frequencies between the patient and control groups and haplotypes associated with disease risk were identified. The SNP rs759330 located 144 bp downstream of BGLAP where it is a predicted microRNA binding site at 3′UTR of PAQR6 – a gene encoding progestin and adipoQ receptor family member VI, was genotyped in 216 patients and 216 control subjects and found to have significant differences in its genotype and allele frequencies (P = 0.0007, OR 2.02 and P = 0.0001, OR 2.02, respectively). Conclusions Our results suggest that these candidate genes are associated with KSD and PAQR6 comes into our view as the most potent candidate since associated SNP rs759330 is located in the miRNA binding site and may affect mRNA expression level. PMID:24886237

[Screening cold-acclimation differential expression candidate genes in the brain of common carp (Cyprinus carpio)].

PubMed

Xu, Li-Hua; Chang, Yu-Mei; Liu, Chun-Lei; Liang, Li-Qun; Liu, Jin-Liang; Chi, Bing-Jie

2011-03-01

In this study, 26 candidate genes were quantified and normalized in the brain cDNA of common carp (Cyprinus carpio) at 23°C and 6°C using double-standard curve method of real-time quantitative PCR. The results showed that five candidates up-regulated in the samples at 6°C (P<0.01) and quantified 2.11, 13.9, 2.52, 7.38, and 1.83 times more than in the samples at 23°C, respectively. Gene function searching indicated that the protein products of these five candidates were elongation of very long chain fatty acids protein, Acyl-CoA desaturase, Transcription initiation factor IIB, Myo-inositol- 1-phosphate synthase, and Blood-brain barrier HT7 antigen individually. Moreover, seven down-regulated candidates were also identified in the same samples at 6°C (P>0.05), and their expression levels were decreased by 21.8%, 25.9%, 16.6%, 23.7%, 15.8%, 16.3%, and 42.5%, respectively, in comparison with the samples at 23°C. These seven down-regulated candidates mainly participated in the inhibition of glycolysis, improvement of cell apoptosis, and intervention of synapse remodeling based on the results of function searching. The five cold-induced genes identified in this study will be used as important elements for fish with cold sensitive through transgenic technology in future.

Identification of Reference Genes for Real-Time Quantitative PCR Experiments in the Liverwort Marchantia polymorpha

PubMed Central

Dolan, Liam; Langdale, Jane A.

2015-01-01

Real-time quantitative polymerase chain reaction (qPCR) has become widely used as a method to compare gene transcript levels across different conditions. However, selection of suitable reference genes to normalize qPCR data is required for accurate transcript level analysis. Recently, Marchantia polymorpha has been adopted as a model for the study of liverwort development and land plant evolution. Identification of appropriate reference genes has therefore become a necessity for gene expression studies. In this study, transcript levels of eleven candidate reference genes have been analyzed across a range of biological contexts that encompass abiotic stress, hormone treatment and different developmental stages. The consistency of transcript levels was assessed using both geNorm and NormFinder algorithms, and a consensus ranking of the different candidate genes was then obtained. MpAPT and MpACT showed relatively constant transcript levels across all conditions tested whereas the transcript levels of other candidate genes were clearly influenced by experimental conditions. By analyzing transcript levels of phosphate and nitrate starvation reporter genes, we confirmed that MpAPT and MpACT are suitable reference genes in M. polymorpha and also demonstrated that normalization with an inappropriate gene can lead to erroneous analysis of qPCR data. PMID:25798897

Cross-platform method for identifying candidate network biomarkers for prostate cancer.

PubMed

Jin, G; Zhou, X; Cui, K; Zhang, X-S; Chen, L; Wong, S T C

2009-11-01

Discovering biomarkers using mass spectrometry (MS) and microarray expression profiles is a promising strategy in molecular diagnosis. Here, the authors proposed a new pipeline for biomarker discovery that integrates disease information for proteins and genes, expression profiles in both genomic and proteomic levels, and protein-protein interactions (PPIs) to discover high confidence network biomarkers. Using this pipeline, a total of 474 molecules (genes and proteins) related to prostate cancer were identified and a prostate-cancer-related network (PCRN) was derived from the integrative information. Thus, a set of candidate network biomarkers were identified from multiple expression profiles composed by eight microarray datasets and one proteomics dataset. The network biomarkers with PPIs can accurately distinguish the prostate patients from the normal ones, which potentially provide more reliable hits of biomarker candidates than conventional biomarker discovery methods.

Analysis of shared homozygosity regions in Saudi siblings with attention deficit hyperactivity disorder

PubMed Central

Al Yemni, Eman A.A.; Alnaemi, Faten M.; Abebe, Dejene; Al-Abdulaziz, Basma S.; Al Mubarak, Bashayer R.; Ghaziuddin, Mohammad; Al Tassan, Nada A.

2017-01-01

Aim Genetic and clinical complexities are common features of most psychiatric illnesses that pose a major obstacle in risk-gene identification. Attention deficit hyperactivity disorder (ADHD) is the most prevalent child-onset psychiatric illness, with high heritability. Over the past decade, numerous genetic studies utilizing various approaches, such as genome-wide association, candidate-gene association, and linkage analysis, have identified a multitude of candidate loci/genes. However, such studies have yielded diverse findings that are rarely reproduced, indicating that other genetic determinants have not been discovered yet. In this study, we carried out sib-pair analysis on seven multiplex families with ADHD from Saudi Arabia. We aimed to identify the candidate chromosomal regions and genes linked to the disease. Patients and methods A total of 41 individuals from multiplex families were analyzed for shared regions of homozygosity. Genes within these regions were prioritized according to their potential relevance to ADHD. Results We identified multiple genomic regions spanning different chromosomes to be shared among affected members of each family; these included chromosomes 3, 5, 6, 7, 8, 9, 10, 13, 17, and 18. We also found specific regions on chromosomes 8 and 17 to be shared between affected individuals from more than one family. Among the genes present in the regions reported here were involved in neurotransmission (GRM3, SIGMAR1, CHAT, and SLC18A3) and members of the HLA gene family (HLA-A, HLA-DPA1, and MICC). Conclusion The candidate regions identified in this study highlight the genetic diversity of ADHD. Upon further investigation, these loci may reveal candidate genes that enclose variants associated with ADHD. Although most ADHD studies were conducted in other populations, our study provides insight from an understudied, ethnically interesting population. PMID:28452824

Prioritization of Disease Susceptibility Genes Using LSM/SVD.

PubMed

Gong, Lejun; Yang, Ronggen; Yan, Qin; Sun, Xiao

2013-12-01

Understanding the role of genetics in diseases is one of the most important tasks in the postgenome era. It is generally too expensive and time consuming to perform experimental validation for all candidate genes related to disease. Computational methods play important roles for prioritizing these candidates. Herein, we propose an approach to prioritize disease genes using latent semantic mapping based on singular value decomposition. Our hypothesis is that similar functional genes are likely to cause similar diseases. Measuring the functional similarity between known disease susceptibility genes and unknown genes is to predict new disease susceptibility genes. Taking autism as an instance, the analysis results of the top ten genes prioritized demonstrate they might be autism susceptibility genes, which also indicates our approach could discover new disease susceptibility genes. The novel approach of disease gene prioritization could discover new disease susceptibility genes, and latent disease-gene relations. The prioritized results could also support the interpretive diversity and experimental views as computational evidence for disease researchers.

Evaluation of Gene-Based Family-Based Methods to Detect Novel Genes Associated With Familial Late Onset Alzheimer Disease

PubMed Central

Fernández, Maria V.; Budde, John; Del-Aguila, Jorge L.; Ibañez, Laura; Deming, Yuetiva; Harari, Oscar; Norton, Joanne; Morris, John C.; Goate, Alison M.; Cruchaga, Carlos

2018-01-01

Gene-based tests to study the combined effect of rare variants on a particular phenotype have been widely developed for case-control studies, but their evolution and adaptation for family-based studies, especially studies of complex incomplete families, has been slower. In this study, we have performed a practical examination of all the latest gene-based methods available for family-based study designs using both simulated and real datasets. We examined the performance of several collapsing, variance-component, and transmission disequilibrium tests across eight different software packages and 22 models utilizing a cohort of 285 families (N = 1,235) with late-onset Alzheimer disease (LOAD). After a thorough examination of each of these tests, we propose a methodological approach to identify, with high confidence, genes associated with the tested phenotype and we provide recommendations to select the best software and model for family-based gene-based analyses. Additionally, in our dataset, we identified PTK2B, a GWAS candidate gene for sporadic AD, along with six novel genes (CHRD, CLCN2, HDLBP, CPAMD8, NLRP9, and MAS1L) as candidate genes for familial LOAD. PMID:29670507

Evaluation of Gene-Based Family-Based Methods to Detect Novel Genes Associated With Familial Late Onset Alzheimer Disease.

PubMed

Fernández, Maria V; Budde, John; Del-Aguila, Jorge L; Ibañez, Laura; Deming, Yuetiva; Harari, Oscar; Norton, Joanne; Morris, John C; Goate, Alison M; Cruchaga, Carlos

2018-01-01

Gene-based tests to study the combined effect of rare variants on a particular phenotype have been widely developed for case-control studies, but their evolution and adaptation for family-based studies, especially studies of complex incomplete families, has been slower. In this study, we have performed a practical examination of all the latest gene-based methods available for family-based study designs using both simulated and real datasets. We examined the performance of several collapsing, variance-component, and transmission disequilibrium tests across eight different software packages and 22 models utilizing a cohort of 285 families ( N = 1,235) with late-onset Alzheimer disease (LOAD). After a thorough examination of each of these tests, we propose a methodological approach to identify, with high confidence, genes associated with the tested phenotype and we provide recommendations to select the best software and model for family-based gene-based analyses. Additionally, in our dataset, we identified PTK2B , a GWAS candidate gene for sporadic AD, along with six novel genes ( CHRD, CLCN2, HDLBP, CPAMD8, NLRP9 , and MAS1L ) as candidate genes for familial LOAD.

Integration of biological data by kernels on graph nodes allows prediction of new genes involved in mitotic chromosome condensation

PubMed Central

Hériché, Jean-Karim; Lees, Jon G.; Morilla, Ian; Walter, Thomas; Petrova, Boryana; Roberti, M. Julia; Hossain, M. Julius; Adler, Priit; Fernández, José M.; Krallinger, Martin; Haering, Christian H.; Vilo, Jaak; Valencia, Alfonso; Ranea, Juan A.; Orengo, Christine; Ellenberg, Jan

2014-01-01

The advent of genome-wide RNA interference (RNAi)–based screens puts us in the position to identify genes for all functions human cells carry out. However, for many functions, assay complexity and cost make genome-scale knockdown experiments impossible. Methods to predict genes required for cell functions are therefore needed to focus RNAi screens from the whole genome on the most likely candidates. Although different bioinformatics tools for gene function prediction exist, they lack experimental validation and are therefore rarely used by experimentalists. To address this, we developed an effective computational gene selection strategy that represents public data about genes as graphs and then analyzes these graphs using kernels on graph nodes to predict functional relationships. To demonstrate its performance, we predicted human genes required for a poorly understood cellular function—mitotic chromosome condensation—and experimentally validated the top 100 candidates with a focused RNAi screen by automated microscopy. Quantitative analysis of the images demonstrated that the candidates were indeed strongly enriched in condensation genes, including the discovery of several new factors. By combining bioinformatics prediction with experimental validation, our study shows that kernels on graph nodes are powerful tools to integrate public biological data and predict genes involved in cellular functions of interest. PMID:24943848

[Discovery of the target genes inhibited by formic acid in Candida shehatae].

PubMed

Cai, Peng; Xiong, Xujie; Xu, Yong; Yong, Qiang; Zhu, Junjun; Shiyuan, Yu

2014-01-04

At transcriptional level, the inhibitory effects of formic acid was investigated on Candida shehatae, a model yeast strain capable of fermenting xylose to ethanol. Thereby, the target genes were regulated by formic acid and the transcript profiles were discovered. On the basis of the transcriptome data of C. shehatae metabolizing glucose and xylose, the genes responsible for ethanol fermentation were chosen as candidates by the combined method of yeast metabolic pathway analysis and manual gene BLAST search. These candidates were then quantitatively detected by RQ-PCR technique to find the regulating genes under gradient doses of formic acid. By quantitative analysis of 42 candidate genes, we finally identified 10 and 5 genes as markedly down-regulated and up-regulated targets by formic acid, respectively. With regard to gene transcripts regulated by formic acid in C. shehatae, the markedly down-regulated genes ranking declines as follows: xylitol dehydrogenase (XYL2), acetyl-CoA synthetase (ACS), ribose-5-phosphate isomerase (RKI), transaldolase (TAL), phosphogluconate dehydrogenase (GND1), transketolase (TKL), glucose-6-phosphate dehydrogenase (ZWF1), xylose reductase (XYL1), pyruvate dehydrogenase (PDH) and pyruvate decarboxylase (PDC); and a declining rank for up-regulated gens as follows: fructose-bisphosphate aldolase (ALD), glucokinase (GLK), malate dehydrogenase (MDH), 6-phosphofructokinase (PFK) and alcohol dehydrogenase (ADH).

Identifying candidate genes for Type 2 Diabetes Mellitus and obesity through gene expression profiling in multiple tissues or cells.

PubMed

Chen, Junhui; Meng, Yuhuan; Zhou, Jinghui; Zhuo, Min; Ling, Fei; Zhang, Yu; Du, Hongli; Wang, Xiaoning

2013-01-01

Type 2 Diabetes Mellitus (T2DM) and obesity have become increasingly prevalent in recent years. Recent studies have focused on identifying causal variations or candidate genes for obesity and T2DM via analysis of expression quantitative trait loci (eQTL) within a single tissue. T2DM and obesity are affected by comprehensive sets of genes in multiple tissues. In the current study, gene expression levels in multiple human tissues from GEO datasets were analyzed, and 21 candidate genes displaying high percentages of differential expression were filtered out. Specifically, DENND1B, LYN, MRPL30, POC1B, PRKCB, RP4-655J12.3, HIBADH, and TMBIM4 were identified from the T2DM-control study, and BCAT1, BMP2K, CSRNP2, MYNN, NCKAP5L, SAP30BP, SLC35B4, SP1, BAP1, GRB14, HSP90AB1, ITGA5, and TOMM5 were identified from the obesity-control study. The majority of these genes are known to be involved in T2DM and obesity. Therefore, analysis of gene expression in various tissues using GEO datasets may be an effective and feasible method to determine novel or causal genes associated with T2DM and obesity.

A comprehensive approach to identify reliable reference gene candidates to investigate the link between alcoholism and endocrinology in Sprague-Dawley rats.

PubMed

Taki, Faten A; Abdel-Rahman, Abdel A; Zhang, Baohong

2014-01-01

Gender and hormonal differences are often correlated with alcohol dependence and related complications like addiction and breast cancer. Estrogen (E2) is an important sex hormone because it serves as a key protein involved in organism level signaling pathways. Alcoholism has been reported to affect estrogen receptor signaling; however, identifying the players involved in such multi-faceted syndrome is complex and requires an interdisciplinary approach. In many situations, preliminary investigations included a straight forward, yet informative biotechniques such as gene expression analyses using quantitative real time PCR (qRT-PCR). The validity of qRT-PCR-based conclusions is affected by the choice of reliable internal controls. With this in mind, we compiled a list of 15 commonly used housekeeping genes (HKGs) as potential reference gene candidates in rat biological models. A comprehensive comparison among 5 statistical approaches (geNorm, dCt method, NormFinder, BestKeeper, and RefFinder) was performed to identify the minimal number as well the most stable reference genes required for reliable normalization in experimental rat groups that comprised sham operated (SO), ovariectomized rats in the absence (OVX) or presence of E2 (OVXE2). These rat groups were subdivided into subgroups that received alcohol in liquid diet or isocalroic control liquid diet for 12 weeks. Our results showed that U87, 5S rRNA, GAPDH, and U5a were the most reliable gene candidates for reference genes in heart and brain tissue. However, different gene stability ranking was specific for each tissue input combination. The present preliminary findings highlight the variability in reference gene rankings across different experimental conditions and analytic methods and constitute a fundamental step for gene expression assays.

No Evidence That Schizophrenia Candidate Genes Are More Associated With Schizophrenia Than Noncandidate Genes.

PubMed

Johnson, Emma C; Border, Richard; Melroy-Greif, Whitney E; de Leeuw, Christiaan A; Ehringer, Marissa A; Keller, Matthew C

2017-11-15

A recent analysis of 25 historical candidate gene polymorphisms for schizophrenia in the largest genome-wide association study conducted to date suggested that these commonly studied variants were no more associated with the disorder than would be expected by chance. However, the same study identified other variants within those candidate genes that demonstrated genome-wide significant associations with schizophrenia. As such, it is possible that variants within historic schizophrenia candidate genes are associated with schizophrenia at levels above those expected by chance, even if the most-studied specific polymorphisms are not. The present study used association statistics from the largest schizophrenia genome-wide association study conducted to date as input to a gene set analysis to investigate whether variants within schizophrenia candidate genes are enriched for association with schizophrenia. As a group, variants in the most-studied candidate genes were no more associated with schizophrenia than were variants in control sets of noncandidate genes. While a small subset of candidate genes did appear to be significantly associated with schizophrenia, these genes were not particularly noteworthy given the large number of more strongly associated noncandidate genes. The history of schizophrenia research should serve as a cautionary tale to candidate gene investigators examining other phenotypes: our findings indicate that the most investigated candidate gene hypotheses of schizophrenia are not well supported by genome-wide association studies, and it is likely that this will be the case for other complex traits as well. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

A comprehensive meta-analysis of plant morphology, yield, stay-green, and virus disease resistance QTL in maize (Zea mays L.).

PubMed

Wang, Yijun; Xu, Jing; Deng, Dexiang; Ding, Haidong; Bian, Yunlong; Yin, Zhitong; Wu, Yarong; Zhou, Bo; Zhao, Ye

2016-02-01

The meta-QTL and candidate genes will facilitate the elucidation of molecular bases underlying agriculturally important traits and open new avenues for functional markers development and elite alleles introgression in maize breeding program. A large number of QTLs attributed to grain productivity and other agriculturally important traits have been identified and deposited in public repositories. The integration of fruitful QTL becomes a major issue in current plant genomics. To this end, we first collected QTL for six agriculturally important traits in maize, including yield, plant height, ear height, leaf angle, stay-green, and maize rough dwarf disease resistance. The meta-analysis method was then employed to retrieve 113 meta-QTL. Additionally, we also isolated candidate genes for target traits by the bioinformatic technique. Several candidates, including some well-characterized genes, GA3ox2 for plant height, lg1 and lg4 for leaf angle, zfl1 and zfl2 for flowering time, were co-localized with established meta-QTL intervals. Intriguingly, in a relatively narrow meta-QTL region, the maize ortholog of rice yield-related gene GW8/OsSPL16 was believed to be a candidate for yield. Leveraging results presented in this study will provide further insights into the genetic architecture of maize agronomic traits. Moreover, the meta-QTL and candidate genes reported here could be harnessed for the enhancement of stress tolerance and yield performance in maize and translation to other crops.

DRD4 and DAT1 in ADHD: Functional neurobiology to pharmacogenetics

PubMed Central

Turic, Darko; Swanson, James; Sonuga-Barke, Edmund

2010-01-01

Attention deficit/hyperactivity disorder (ADHD) is a common and potentially very impairing neuropsychiatric disorder of childhood. Statistical genetic studies of twins have shown ADHD to be highly heritable, with the combination of genes and gene by environment interactions accounting for around 80% of phenotypic variance. The initial molecular genetic studies where candidates were selected because of the efficacy of dopaminergic compounds in the treatment of ADHD were remarkably successful and provided strong evidence for the role of DRD4 and DAT1 variants in the pathogenesis of ADHD. However, the recent application of non-candidate gene strategies (eg, genome-wide association scans) has failed to identify additional genes with substantial genetic main effects, and the effects for DRD4 and DAT1 have not been replicated. This is the usual pattern observed for most other physical and mental disorders evaluated with current state-of-the-art methods. In this paper we discuss future strategies for genetic studies in ADHD, highlighting both the pitfalls and possible solutions relating to candidate gene studies, genome-wide studies, defining the phenotype, and statistical approaches. PMID:23226043

An Arrayed Genome-Scale Lentiviral-Enabled Short Hairpin RNA Screen Identifies Lethal and Rescuer Gene Candidates

PubMed Central

Bhinder, Bhavneet; Antczak, Christophe; Ramirez, Christina N.; Shum, David; Liu-Sullivan, Nancy; Radu, Constantin; Frattini, Mark G.

2013-01-01

Abstract RNA interference technology is becoming an integral tool for target discovery and validation.; With perhaps the exception of only few studies published using arrayed short hairpin RNA (shRNA) libraries, most of the reports have been either against pooled siRNA or shRNA, or arrayed siRNA libraries. For this purpose, we have developed a workflow and performed an arrayed genome-scale shRNA lethality screen against the TRC1 library in HeLa cells. The resulting targets would be a valuable resource of candidates toward a better understanding of cellular homeostasis. Using a high-stringency hit nomination method encompassing criteria of at least three active hairpins per gene and filtered for potential off-target effects (OTEs), referred to as the Bhinder–Djaballah analysis method, we identified 1,252 lethal and 6 rescuer gene candidates, knockdown of which resulted in severe cell death or enhanced growth, respectively. Cross referencing individual hairpins with the TRC1 validated clone database, 239 of the 1,252 candidates were deemed independently validated with at least three validated clones. Through our systematic OTE analysis, we have identified 31 microRNAs (miRNAs) in lethal and 2 in rescuer genes; all having a seed heptamer mimic in the corresponding shRNA hairpins and likely cause of the OTE observed in our screen, perhaps unraveling a previously unknown plausible essentiality of these miRNAs in cellular viability. Taken together, we report on a methodology for performing large-scale arrayed shRNA screens, a comprehensive analysis method to nominate high-confidence hits, and a performance assessment of the TRC1 library highlighting the intracellular inefficiencies of shRNA processing in general. PMID:23198867

An extensive analysis of disease-gene associations using network integration and fast kernel-based gene prioritization methods.

PubMed

Valentini, Giorgio; Paccanaro, Alberto; Caniza, Horacio; Romero, Alfonso E; Re, Matteo

2014-06-01

In the context of "network medicine", gene prioritization methods represent one of the main tools to discover candidate disease genes by exploiting the large amount of data covering different types of functional relationships between genes. Several works proposed to integrate multiple sources of data to improve disease gene prioritization, but to our knowledge no systematic studies focused on the quantitative evaluation of the impact of network integration on gene prioritization. In this paper, we aim at providing an extensive analysis of gene-disease associations not limited to genetic disorders, and a systematic comparison of different network integration methods for gene prioritization. We collected nine different functional networks representing different functional relationships between genes, and we combined them through both unweighted and weighted network integration methods. We then prioritized genes with respect to each of the considered 708 medical subject headings (MeSH) diseases by applying classical guilt-by-association, random walk and random walk with restart algorithms, and the recently proposed kernelized score functions. The results obtained with classical random walk algorithms and the best single network achieved an average area under the curve (AUC) across the 708 MeSH diseases of about 0.82, while kernelized score functions and network integration boosted the average AUC to about 0.89. Weighted integration, by exploiting the different "informativeness" embedded in different functional networks, outperforms unweighted integration at 0.01 significance level, according to the Wilcoxon signed rank sum test. For each MeSH disease we provide the top-ranked unannotated candidate genes, available for further bio-medical investigation. Network integration is necessary to boost the performances of gene prioritization methods. Moreover the methods based on kernelized score functions can further enhance disease gene ranking results, by adopting both local and global learning strategies, able to exploit the overall topology of the network. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Identification and fine mapping of a stay-green gene (Brnye1) in pakchoi (Brassica campestris L. ssp. chinensis).

PubMed

Wang, Nan; Liu, Zhiyong; Zhang, Yun; Li, Chengyu; Feng, Hui

2018-03-01

Using bulked segregant analysis combined with next-generation sequencing, we delimited the Brnye1 gene responsible for the stay-green trait of nye in pakchoi. Sequence analysis identified Bra019346 as the candidate gene. "Stay-green" refers to a plant trait whereby leaves remain green during senescence. This trait is useful in the cultivation of pakchoi (Brassica campestris L. ssp. chinensis), which is marketed as a green leaf product. This study aimed to identify the gene responsible for the stay-green trait in pakchoi. We identified a stay-green mutant in pakchoi, which we termed "nye". Genetic analysis revealed that the stay-green trait is controlled by a single recessive gene, Brnye1. Using the BSA-seq method, a 3.0-Mb candidate region was mapped on chromosome A03, which helped us localize Brnye1 to an 81.01-kb interval between SSR markers SSRWN27 and SSRWN30 via linkage analysis in an F 2 population. We identified 12 genes in this region, 11 of which were annotated based on the Brassica rapa annotation database, and one was a functionally unknown gene. An orthologous gene of the Arabidopsis gene AtNYE1, Bra019346, was identified as the potential candidate for Brnye1. Sequence analysis revealed a 40-bp insertion in the second exon of Bra019346 in nye, which generated the TAA stop codon. A candidate gene-specific Indel marker in 1561 F 2 individuals showed perfect cosegregation with Brnye1 in the nye mutant. These results provide a foundation for uncovering the molecular mechanism of the stay-green trait in pakchoi.

Discovering novel subsystems using comparative genomics

PubMed Central

Ferrer, Luciana; Shearer, Alexander G.; Karp, Peter D.

2011-01-01

Motivation: Key problems for computational genomics include discovering novel pathways in genome data, and discovering functional interaction partners for genes to define new members of partially elucidated pathways. Results: We propose a novel method for the discovery of subsystems from annotated genomes. For each gene pair, a score measuring the likelihood that the two genes belong to a same subsystem is computed using genome context methods. Genes are then grouped based on these scores, and the resulting groups are filtered to keep only high-confidence groups. Since the method is based on genome context analysis, it relies solely on structural annotation of the genomes. The method can be used to discover new pathways, find missing genes from a known pathway, find new protein complexes or other kinds of functional groups and assign function to genes. We tested the accuracy of our method in Escherichia coli K-12. In one configuration of the system, we find that 31.6% of the candidate groups generated by our method match a known pathway or protein complex closely, and that we rediscover 31.2% of all known pathways and protein complexes of at least 4 genes. We believe that a significant proportion of the candidates that do not match any known group in E.coli K-12 corresponds to novel subsystems that may represent promising leads for future laboratory research. We discuss in-depth examples of these findings. Availability: Predicted subsystems are available at http://brg.ai.sri.com/pwy-discovery/journal.html. Contact: lferrer@ai.sri.com Supplementary information: Supplementary data are available at Bioinformatics online. PMID:21775308

Transcriptome sequencing of three Ranunculus species (Ranunculaceae) reveals candidate genes in adaptation from terrestrial to aquatic habitats

PubMed Central

Chen, Ling-Yun; Zhao, Shu-Ying; Wang, Qing-Feng; Moody, Michael L.

2015-01-01

Adaptation to aquatic habitats is a formidable challenge for terrestrial angiosperms that has long intrigued scientists. As part of a suite of work to explore the molecular mechanism of adaptation to aquatic habitats, we here sequenced the transcriptome of the submerged aquatic plant Ranunculus bungei, and two terrestrial relatives R. cantoniensis and R. brotherusii, followed by comparative evolutionary analyses to determine candidate genes for adaption to aquatic habitats. We obtained 126,037, 140,218 and 114,753 contigs for R. bungei, R. cantoniensis and R. brotherusii respectively. Bidirectional Best Hit method and OrthoMCL method identified 11,362 and 8,174 1:1:1 orthologous genes (one ortholog is represented in each of the three species) respectively. Non-synonymous/synonymous (dN/dS) analyses were performed with a maximum likelihood method and an approximate method for the three species-pairs. In total, 14 genes of R. bungei potentially involved in the adaptive transition from terrestrial to aquatic habitats were identified. Some of the homologs to these genes in model plants are involved in vacuole protein formation, regulating ‘water transport process’ and ‘microtubule cytoskeleton organization’. Our study opens the door to understand the molecular mechanism of plant adaptation from terrestrial to aquatic habitats. PMID:25993393

Identification of a Novel De Novo Heterozygous Deletion in the SOX10 Gene in Waardenburg Syndrome Type II Using Next-Generation Sequencing.

PubMed

Li, Haonan; Jin, Peng; Hao, Qian; Zhu, Wei; Chen, Xia; Wang, Ping

2017-11-01

Waardenburg syndrome (WS) is a rare autosomal dominant disorder associated with pigmentation abnormalities and sensorineural hearing loss. In this study, we investigated the genetic cause of WSII in a patient and evaluated the reliability of the targeted next-generation exome sequencing method for the genetic diagnosis of WS. Clinical evaluations were conducted on the patient and targeted next-generation sequencing (NGS) was used to identify the candidate genes responsible for WSII. Multiplex ligation-dependent probe amplification (MLPA) and real-time quantitative polymerase chain reaction (qPCR) were performed to confirm the targeted NGS results. Targeted NGS detected the entire deletion of the coding sequence (CDS) of the SOX10 gene in the WSII patient. MLPA results indicated that all exons of the SOX10 heterozygous deletion were detected; no aberrant copy number in the PAX3 and microphthalmia-associated transcription factor (MITF) genes was found. Real-time qPCR results identified the mutation as a de novo heterozygous deletion. This is the first report of using a targeted NGS method for WS candidate gene sequencing; its accuracy was verified by using the MLPA and qPCR methods. Our research provides a valuable method for the genetic diagnosis of WS.

In Vitro Evaluation of Glycoengineered RSV-F in the Human Artificial Lymph Node Reactor.

PubMed

Radke, Lars; Sandig, Grit; Lubitz, Annika; Schließer, Ulrike; von Horsten, Hans Henning; Blanchard, Veronique; Keil, Karolin; Sandig, Volker; Giese, Christoph; Hummel, Michael; Hinderlich, Stephan; Frohme, Marcus

2017-08-15

Subunit vaccines often require adjuvants to elicit sustained immune activity. Here, a method is described to evaluate the efficacy of single vaccine candidates in the preclinical stage based on cytokine and gene expression analysis. As a model, the recombinant human respiratory syncytial virus (RSV) fusion protein (RSV-F) was produced in CHO cells. For comparison, wild-type and glycoengineered, afucosylated RSV-F were established. Both glycoprotein vaccines were tested in a commercial Human Artificial Lymph Node in vitro model (HuALN ® ). The analysis of six key cytokines in cell culture supernatants showed well-balanced immune responses for the afucosylated RSV-F, while immune response of wild-type RSV-F was more Th1 accentuated. In particular, stronger and specific secretion of interleukin-4 after each round of re-stimulation underlined higher potency and efficacy of the afucosylated vaccine candidate. Comprehensive gene expression analysis by nCounter gene expression assay confirmed the stronger onset of the immunologic reaction in stimulation experiments with the afucosylated vaccine in comparison to wild-type RSV-F and particularly revealed prominent activation of Th17 related genes, innate immunity, and comprehensive activation of humoral immunity. We, therefore, show that our method is suited to distinguish the potency of two vaccine candidates with minor structural differences.

Identification and validation of reference genes for normalization of gene expression analysis using qRT-PCR in Helicoverpa armigera (Lepidoptera: Noctuidae).

PubMed

Zhang, Songdou; An, Shiheng; Li, Zhen; Wu, Fengming; Yang, Qingpo; Liu, Yichen; Cao, Jinjun; Zhang, Huaijiang; Zhang, Qingwen; Liu, Xiaoxia

2015-01-25

Recent studies have focused on determining functional genes and microRNAs in the pest Helicoverpa armigera (Lepidoptera: Noctuidae). Most of these studies used quantitative real-time PCR (qRT-PCR). Suitable reference genes are necessary to normalize gene expression data of qRT-PCR. However, a comprehensive study on the reference genes in H. armigera remains lacking. Twelve candidate reference genes of H. armigera were selected and evaluated for their expression stability under different biotic and abiotic conditions. The comprehensive stability ranking of candidate reference genes was recommended by RefFinder and the optimal number of reference genes was calculated by geNorm. Two target genes, thioredoxin (TRX) and Cu/Zn superoxide dismutase (SOD), were used to validate the selection of reference genes. Results showed that the most suitable candidate combinations of reference genes were as follows: 28S and RPS15 for developmental stages; RPS15 and RPL13 for larvae tissues; EF and RPL27 for adult tissues; GAPDH, RPL27, and β-TUB for nuclear polyhedrosis virus infection; RPS15 and RPL32 for insecticide treatment; RPS15 and RPL27 for temperature treatment; and RPL32, RPS15, and RPL27 for all samples. This study not only establishes an accurate method for normalizing qRT-PCR data in H. armigera but also serve as a reference for further study on gene transcription in H. armigera and other insects. Copyright © 2014 Elsevier B.V. All rights reserved.

Inferring Gene Regulatory Networks by Singular Value Decomposition and Gravitation Field Algorithm

PubMed Central

Zheng, Ming; Wu, Jia-nan; Huang, Yan-xin; Liu, Gui-xia; Zhou, You; Zhou, Chun-guang

2012-01-01

Reconstruction of gene regulatory networks (GRNs) is of utmost interest and has become a challenge computational problem in system biology. However, every existing inference algorithm from gene expression profiles has its own advantages and disadvantages. In particular, the effectiveness and efficiency of every previous algorithm is not high enough. In this work, we proposed a novel inference algorithm from gene expression data based on differential equation model. In this algorithm, two methods were included for inferring GRNs. Before reconstructing GRNs, singular value decomposition method was used to decompose gene expression data, determine the algorithm solution space, and get all candidate solutions of GRNs. In these generated family of candidate solutions, gravitation field algorithm was modified to infer GRNs, used to optimize the criteria of differential equation model, and search the best network structure result. The proposed algorithm is validated on both the simulated scale-free network and real benchmark gene regulatory network in networks database. Both the Bayesian method and the traditional differential equation model were also used to infer GRNs, and the results were used to compare with the proposed algorithm in our work. And genetic algorithm and simulated annealing were also used to evaluate gravitation field algorithm. The cross-validation results confirmed the effectiveness of our algorithm, which outperforms significantly other previous algorithms. PMID:23226565

Screening for microsatellite instability target genes in colorectal cancers

PubMed Central

Vilkki, S; Launonen, V; Karhu, A; Sistonen, P; Vastrik, I; Aaltonen, L

2002-01-01

Background: Defects in the DNA repair system lead to genetic instability because replication errors are not corrected. This type of genetic instability is a key event in the malignant progression of HNPCC and a subset of sporadic colon cancers and mutation rates are particularly high at short repetitive sequences. Somatic deletions of coding mononucleotide repeats have been detected, for example, in the TGFßRII and BAX genes, and recently many novel target genes for microsatellite instability (MSI) have been proposed. Novel target genes are likely to be discovered in the future. More data should be created on background mutation rates in MSI tumours to evaluate mutation rates observed in the candidate target genes. Methods: Mutation rates in 14 neutral intronic repeats were evaluated in MSI tumours. Bioinformatic searches combined with keywords related to cancer and tumour suppressor or CRC related gene homology were used to find new candidate MSI target genes. By comparison of mutation frequencies observed in intronic mononucleotide repeats versus exonic coding repeats of potential MSI target genes, the significance of the exonic mutations was estimated. Results: As expected, the length of an intronic mononucleotide repeat correlated positively with the number of slippages for both G/C and A/T repeats (p=0.0020 and p=0.0012, respectively). BRCA1, CtBP1, and Rb1 associated CtIP and other candidates were found in a bioinformatic search combined with keywords related to cancer. Sequencing showed a significantly increased mutation rate in the exonic A9 repeat of CtIP (25/109=22.9%) as compared with similar intronic repeats (p≤0.001). Conclusions: We propose a new candidate MSI target gene CtIP to be evaluated in further studies. PMID:12414815

Getting the most out of RNA-seq data analysis.

PubMed

Khang, Tsung Fei; Lau, Ching Yee

2015-01-01

Background. A common research goal in transcriptome projects is to find genes that are differentially expressed in different phenotype classes. Biologists might wish to validate such gene candidates experimentally, or use them for downstream systems biology analysis. Producing a coherent differential gene expression analysis from RNA-seq count data requires an understanding of how numerous sources of variation such as the replicate size, the hypothesized biological effect size, and the specific method for making differential expression calls interact. We believe an explicit demonstration of such interactions in real RNA-seq data sets is of practical interest to biologists. Results. Using two large public RNA-seq data sets-one representing strong, and another mild, biological effect size-we simulated different replicate size scenarios, and tested the performance of several commonly-used methods for calling differentially expressed genes in each of them. We found that, when biological effect size was mild, RNA-seq experiments should focus on experimental validation of differentially expressed gene candidates. Importantly, at least triplicates must be used, and the differentially expressed genes should be called using methods with high positive predictive value (PPV), such as NOISeq or GFOLD. In contrast, when biological effect size was strong, differentially expressed genes mined from unreplicated experiments using NOISeq, ASC and GFOLD had between 30 to 50% mean PPV, an increase of more than 30-fold compared to the cases of mild biological effect size. Among methods with good PPV performance, having triplicates or more substantially improved mean PPV to over 90% for GFOLD, 60% for DESeq2, 50% for NOISeq, and 30% for edgeR. At a replicate size of six, we found DESeq2 and edgeR to be reasonable methods for calling differentially expressed genes at systems level analysis, as their PPV and sensitivity trade-off were superior to the other methods'. Conclusion. When biological effect size is weak, systems level investigation is not possible using RNAseq data, and no meaningful result can be obtained in unreplicated experiments. Nonetheless, NOISeq or GFOLD may yield limited numbers of gene candidates with good validation potential, when triplicates or more are available. When biological effect size is strong, NOISeq and GFOLD are effective tools for detecting differentially expressed genes in unreplicated RNA-seq experiments for qPCR validation. When triplicates or more are available, GFOLD is a sharp tool for identifying high confidence differentially expressed genes for targeted qPCR validation; for downstream systems level analysis, combined results from DESeq2 and edgeR are useful.

A role for genetic susceptibility in sporadic focal segmental glomerulosclerosis

PubMed Central

Yu, Haiyang; Artomov, Mykyta; Brähler, Sebastian; Stander, M. Christine; Shamsan, Ghaidan; Sampson, Matthew G.; White, J. Michael; Kretzler, Matthias; Jain, Sanjay; Winkler, Cheryl A.; Mitra, Robi D.; Daly, Mark J.; Shaw, Andrey S.

2016-01-01

Focal segmental glomerulosclerosis (FSGS) is a syndrome that involves kidney podocyte dysfunction and causes chronic kidney disease. Multiple factors including chemical toxicity, inflammation, and infection underlie FSGS; however, highly penetrant disease genes have been identified in a small fraction of patients with a family history of FSGS. Variants of apolipoprotein L1 (APOL1) have been linked to FSGS in African Americans with HIV or hypertension, supporting the proposal that genetic factors enhance FSGS susceptibility. Here, we used sequencing to investigate whether genetics plays a role in the majority of FSGS cases that are identified as primary or sporadic FSGS and have no known cause. Given the limited number of biopsy-proven cases with ethnically matched controls, we devised an analytic strategy to identify and rank potential candidate genes and used an animal model for validation. Nine candidate FSGS susceptibility genes were identified in our patient cohort, and three were validated using a high-throughput mouse method that we developed. Specifically, we introduced a podocyte-specific, doxycycline-inducible transactivator into a murine embryonic stem cell line with an FSGS-susceptible genetic background that allows shRNA-mediated targeting of candidate genes in the adult kidney. Our analysis supports a broader role for genetic susceptibility of both sporadic and familial cases of FSGS and provides a tool to rapidly evaluate candidate FSGS-associated genes. PMID:26901816

No Association of BDNF, COMT, MAOA, SLC6A3, and SLC6A4 Genes and Depressive Symptoms in a Sample of Healthy Colombian Subjects.

PubMed

González-Giraldo, Yeimy; Camargo, Andrés; López-León, Sandra; Forero, Diego A

2015-01-01

Background. Major depressive disorder (MDD) is the second cause of years lived with disability around the world. A large number of studies have been carried out to identify genetic risk factors for MDD and related endophenotypes, mainly in populations of European and Asian descent, with conflicting results. The main aim of the current study was to analyze the possible association of five candidate genes and depressive symptoms in a Colombian sample of healthy subjects. Methods and Materials. The Spanish adaptation of the Hospital Anxiety and Depression Scale (HADS) was applied to one hundred eighty-eight healthy Colombian subjects. Five functional polymorphisms were genotyped using PCR-based assays: BDNF-Val66Met (rs6265), COMT-Val158Met (rs4680), SLC6A4-HTTLPR (rs4795541), MAOA-uVNTR, and SLC6A3-VNTR (rs28363170). Result. We did not find significant associations with scores of depressive symptoms, derived from the HADS, for any of the five candidate genes (nominal p values >0.05). In addition, we did not find evidence of significant gene-gene interactions. Conclusion. This work is one of the first studies of candidate genes for depressive symptoms in a Latin American sample. Study of additional genetic and epigenetic variants, taking into account other pathophysiological theories, will help to identify novel candidates for MDD in populations around the world.

Validation of reference genes for accurate normalization of gene expression for real time-quantitative PCR in strawberry fruits using different cultivars and osmotic stresses.

PubMed

Galli, Vanessa; Borowski, Joyce Moura; Perin, Ellen Cristina; Messias, Rafael da Silva; Labonde, Julia; Pereira, Ivan dos Santos; Silva, Sérgio Delmar Dos Anjos; Rombaldi, Cesar Valmor

2015-01-10

The increasing demand of strawberry (Fragaria×ananassa Duch) fruits is associated mainly with their sensorial characteristics and the content of antioxidant compounds. Nevertheless, the strawberry production has been hampered due to its sensitivity to abiotic stresses. Therefore, to understand the molecular mechanisms highlighting stress response is of great importance to enable genetic engineering approaches aiming to improve strawberry tolerance. However, the study of expression of genes in strawberry requires the use of suitable reference genes. In the present study, seven traditional and novel candidate reference genes were evaluated for transcript normalization in fruits of ten strawberry cultivars and two abiotic stresses, using RefFinder, which integrates the four major currently available software programs: geNorm, NormFinder, BestKeeper and the comparative delta-Ct method. The results indicate that the expression stability is dependent on the experimental conditions. The candidate reference gene DBP (DNA binding protein) was considered the most suitable to normalize expression data in samples of strawberry cultivars and under drought stress condition, and the candidate reference gene HISTH4 (histone H4) was the most stable under osmotic stresses and salt stress. The traditional genes GAPDH (glyceraldehyde-3-phosphate dehydrogenase) and 18S (18S ribosomal RNA) were considered the most unstable genes in all conditions. The expression of phenylalanine ammonia lyase (PAL) and 9-cis epoxycarotenoid dioxygenase (NCED1) genes were used to further confirm the validated candidate reference genes, showing that the use of an inappropriate reference gene may induce erroneous results. This study is the first survey on the stability of reference genes in strawberry cultivars and osmotic stresses and provides guidelines to obtain more accurate RT-qPCR results for future breeding efforts. Copyright © 2014 Elsevier B.V. All rights reserved.

Evaluation of two mutants of Mycobacterium avium subsp. paratuberculosis as candidates for a live attenuated vaccine for Johne's disease

USDA-ARS?s Scientific Manuscript database

Efforts to control Johne’s disease (JD), caused by Mycobacterium avium subsp. paratuberculosis (Map), has been difficult because of a lack of an effective vaccine. To address this problem we examined the potential of targeted gene disruption as a method to develop candidate vaccines with impaired c...

A Novel Yeast Genomics Method for Identifying New Breast Cancer Susceptibility Genes

DTIC Science & Technology

2007-05-01

find new candidate genes for breast cancer susceptibility in women and identifying these human genes can further improve monitoring and treatment...breast cancer susceptibility genes in humans that are currently unknown and not deducible from current methodologies. It is a fundamental...template to faithfully repair the broken strand. In human cancer it is loss of HR, rather than NHEJ, that is more important in increasing cancer

Comprehensive analysis of alternative splicing and functionality in neuronal differentiation of P19 cells.

PubMed

Suzuki, Hitoshi; Osaki, Ken; Sano, Kaori; Alam, A H M Khurshid; Nakamura, Yuichiro; Ishigaki, Yasuhito; Kawahara, Kozo; Tsukahara, Toshifumi

2011-02-18

Alternative splicing, which produces multiple mRNAs from a single gene, occurs in most human genes and contributes to protein diversity. Many alternative isoforms are expressed in a spatio-temporal manner, and function in diverse processes, including in the neural system. The purpose of the present study was to comprehensively investigate neural-splicing using P19 cells. GeneChip Exon Array analysis was performed using total RNAs purified from cells during neuronal cell differentiation. To efficiently and readily extract the alternative exon candidates, 9 filtering conditions were prepared, yielding 262 candidate exons (236 genes). Semiquantitative RT-PCR results in 30 randomly selected candidates suggested that 87% of the candidates were differentially alternatively spliced in neuronal cells compared to undifferentiated cells. Gene ontology and pathway analyses suggested that many of the candidate genes were associated with neural events. Together with 66 genes whose functions in neural cells or organs were reported previously, 47 candidate genes were found to be linked to 189 events in the gene-level profile of neural differentiation. By text-mining for the alternative isoform, distinct functions of the isoforms of 9 candidate genes indicated by the result of Exon Array were confirmed. Alternative exons were successfully extracted. Results from the informatics analyses suggested that neural events were primarily governed by genes whose expression was increased and whose transcripts were differentially alternatively spliced in the neuronal cells. In addition to known functions in neural cells or organs, the uninvestigated alternative splicing events of 11 genes among 47 candidate genes suggested that cell cycle events are also potentially important. These genes may help researchers to differentiate the roles of alternative splicing in cell differentiation and cell proliferation.

Novel candidate genes important for asthma and hypertension comorbidity revealed from associative gene networks.

PubMed

Saik, Olga V; Demenkov, Pavel S; Ivanisenko, Timofey V; Bragina, Elena Yu; Freidin, Maxim B; Goncharova, Irina A; Dosenko, Victor E; Zolotareva, Olga I; Hofestaedt, Ralf; Lavrik, Inna N; Rogaev, Evgeny I; Ivanisenko, Vladimir A

2018-02-13

Hypertension and bronchial asthma are a major issue for people's health. As of 2014, approximately one billion adults, or ~ 22% of the world population, have had hypertension. As of 2011, 235-330 million people globally have been affected by asthma and approximately 250,000-345,000 people have died each year from the disease. The development of the effective treatment therapies against these diseases is complicated by their comorbidity features. This is often a major problem in diagnosis and their treatment. Hence, in this study the bioinformatical methodology for the analysis of the comorbidity of these two diseases have been developed. As such, the search for candidate genes related to the comorbid conditions of asthma and hypertension can help in elucidating the molecular mechanisms underlying the comorbid condition of these two diseases, and can also be useful for genotyping and identifying new drug targets. Using ANDSystem, the reconstruction and analysis of gene networks associated with asthma and hypertension was carried out. The gene network of asthma included 755 genes/proteins and 62,603 interactions, while the gene network of hypertension - 713 genes/proteins and 45,479 interactions. Two hundred and five genes/proteins and 9638 interactions were shared between asthma and hypertension. An approach for ranking genes implicated in the comorbid condition of two diseases was proposed. The approach is based on nine criteria for ranking genes by their importance, including standard methods of gene prioritization (Endeavor, ToppGene) as well as original criteria that take into account the characteristics of an associative gene network and the presence of known polymorphisms in the analysed genes. According to the proposed approach, the genes IL10, TLR4, and CAT had the highest priority in the development of comorbidity of these two diseases. Additionally, it was revealed that the list of top genes is enriched with apoptotic genes and genes involved in biological processes related to the functioning of central nervous system. The application of methods of reconstruction and analysis of gene networks is a productive tool for studying the molecular mechanisms of comorbid conditions. The method put forth to rank genes by their importance to the comorbid condition of asthma and hypertension was employed that resulted in prediction of 10 genes, playing the key role in the development of the comorbid condition. The results can be utilised to plan experiments for identification of novel candidate genes along with searching for novel pharmacological targets.

Candidate gene biodosimetry markers of exposure to external ionizing radiation in human blood: A systematic review

PubMed Central

Sima, Chao; Amundson, Sally A.; Zenhausern, Frederic

2018-01-01

Purpose To compile a list of genes that have been reported to be affected by external ionizing radiation (IR) and to assess their performance as candidate biomarkers for individual human radiation dosimetry. Methods Eligible studies were identified through extensive searches of the online databases from 1978 to 2017. Original English-language publications of microarray studies assessing radiation-induced changes in gene expression levels in human blood after external IR were included. Genes identified in at least half of the selected studies were retained for bio-statistical analysis in order to evaluate their diagnostic ability. Results 24 studies met the criteria and were included in this study. Radiation-induced expression of 10,170 unique genes was identified and the 31 genes that have been identified in at least 50% of studies (12/24 studies) were selected for diagnostic power analysis. Twenty-seven genes showed a significant Spearman’s correlation with radiation dose. Individually, TNFSF4, FDXR, MYC, ZMAT3 and GADD45A provided the best discrimination of radiation dose < 2 Gy and dose ≥ 2 Gy according to according to their maximized Youden’s index (0.67, 0.55, 0.55, 0.55 and 0.53 respectively). Moreover, 12 combinations of three genes display an area under the Receiver Operating Curve (ROC) curve (AUC) = 1 reinforcing the concept of biomarker combinations instead of looking for an ideal and unique biomarker. Conclusion Gene expression is a promising approach for radiation dosimetry assessment. A list of robust candidate biomarkers has been identified from analysis of the studies published to date, confirming for example the potential of well-known genes such as FDXR and TNFSF4 or highlighting other promising gene such as ZMAT3. However, heterogeneity in protocols and analysis methods will require additional studies to confirm these results. PMID:29879226

NCG 4.0: the network of cancer genes in the era of massive mutational screenings of cancer genomes

PubMed Central

An, Omer; Pendino, Vera; D’Antonio, Matteo; Ratti, Emanuele; Gentilini, Marco; Ciccarelli, Francesca D.

2014-01-01

NCG 4.0 is the latest update of the Network of Cancer Genes, a web-based repository of systems-level properties of cancer genes. In its current version, the database collects information on 537 known (i.e. experimentally supported) and 1463 candidate (i.e. inferred using statistical methods) cancer genes. Candidate cancer genes derive from the manual revision of 67 original publications describing the mutational screening of 3460 human exomes and genomes in 23 different cancer types. For all 2000 cancer genes, duplicability, evolutionary origin, expression, functional annotation, interaction network with other human proteins and with microRNAs are reported. In addition to providing a substantial update of cancer-related information, NCG 4.0 also introduces two new features. The first is the annotation of possible false-positive cancer drivers, defined as candidate cancer genes inferred from large-scale screenings whose association with cancer is likely to be spurious. The second is the description of the systems-level properties of 64 human microRNAs that are causally involved in cancer progression (oncomiRs). Owing to the manual revision of all information, NCG 4.0 constitutes a complete and reliable resource on human coding and non-coding genes whose deregulation drives cancer onset and/or progression. NCG 4.0 can also be downloaded as a free application for Android smart phones. Database URL: http://bio.ieo.eu/ncg/ PMID:24608173

Candidate genetic modifiers for breast and ovarian cancer risk in BRCA1 and BRCA2 mutation carriers

PubMed Central

Peterlongo, Paolo; Chang-Claude, Jenny; Moysich, Kirsten B.; Rudolph, Anja; Schmutzler, Rita K.; Simard, Jacques; Soucy, Penny; Eeles, Rosalind A.; Easton, Douglas F.; Hamann, Ute; Wilkening, Stefan; Chen, Bowang; Rookus, Matti A.; Schmidt, Marjanka K; van der Baan, Frederieke H.; Spurdle, Amanda B.; Walker, Logan C.; Lose, Felicity; Maia, Ana-Teresa; Montagna, Marco; Matricardi, Laura; Lubinski, Jan; Jakubowska, Anna; Gómez Garcia, Encarna B.; Olopade, Olufunmilayo I.; Nussbaum, Robert L.; Nathanson, Katherine L.; Domchek, Susan M.; Rebbeck, Timothy R.; Arun, Banu K.; Karlan, Beth Y.; Orsulic, Sandra; Lester, Jenny; Chung, Wendy K.; Miron, Alex; Southey, Melissa C.; Goldgar, David E.; Buys, Saundra S.; Janavicius, Ramunas; Dorfling, Cecilia M.; van Rensburg, Elizabeth J.; Ding, Yuan Chun; Neuhausen, Susan L.; Hansen, Thomas V. O.; Gerdes, Anne-Marie; Ejlertsen, Bent; Jønson, Lars; Osorio, Ana; Martínez-Bouzas, Cristina; Benitez, Javier; Conway, Edye E.; Blazer, Kathleen R.; Weitzel, Jeffrey N.; Manoukian, Siranoush; Peissel, Bernard; Zaffaroni, Daniela; Scuvera, Giulietta; Barile, Monica; Ficarazzi, Filomena; Mariette, Frederique; Fortuzzi, Stefano; Viel, Alessandra; Giannini, Giuseppe; Papi, Laura; Martayan, Aline; Tibiletti, Maria Grazia; Radice, Paolo; Vratimos, Athanassios; Fostira, Florentia; Garber, Judy E.; Donaldson, Alan; Brewer, Carole; Foo, Claire; Evans, D. Gareth R.; Frost, Debra; Eccles, Diana; Brady, Angela; Cook, Jackie; Tischkowitz, Marc; Adlard, Julian; Barwell, Julian; Walker, Lisa; Izatt, Louise; Side, Lucy E.; Kennedy, M. John; Rogers, Mark T.; Porteous, Mary E.; Morrison, Patrick J.; Platte, Radka; Davidson, Rosemarie; Hodgson, Shirley V.; Ellis, Steve; Cole, Trevor; Godwin, Andrew K.; Claes, Kathleen; Van Maerken, Tom; Meindl, Alfons; Gehrig, Andrea; Sutter, Christian; Engel, Christoph; Niederacher, Dieter; Steinemann, Doris; Plendl, Hansjoerg; Kast, Karin; Rhiem, Kerstin; Ditsch, Nina; Arnold, Norbert; Varon-Mateeva, Raymonda; Wappenschmidt, Barbara; Wang-Gohrke, Shan; Bressac-de Paillerets, Brigitte; Buecher, Bruno; Delnatte, Capucine; Houdayer, Claude; Stoppa-Lyonnet, Dominique; Damiola, Francesca; Coupier, Isabelle; Barjhoux, Laure; Venat-Bouvet, Laurence; Golmard, Lisa; Boutry-Kryza, Nadia; Sinilnikova, Olga M.; Caron, Olivier; Pujol, Pascal; Mazoyer, Sylvie; Belotti, Muriel; Piedmonte, Marion; Friedlander, Michael L.; Rodriguez, Gustavo C.; Copeland, Larry J; de la Hoya, Miguel; Segura, Pedro Perez; Nevanlinna, Heli; Aittomäki, Kristiina; van Os, Theo A.M.; Meijers-Heijboer, Hanne E.J.; van der Hout, Annemarie H.; Vreeswijk, Maaike P.G.; Hoogerbrugge, Nicoline; Ausems, Margreet G.E.M.; van Doorn, Helena C.; Collée, J. Margriet; Olah, Edith; Diez, Orland; Blanco, Ignacio; Lazaro, Conxi; Brunet, Joan; Feliubadalo, Lidia; Cybulski, Cezary; Gronwald, Jacek; Durda, Katarzyna; Jaworska-Bieniek, Katarzyna; Sukiennicki, Grzegorz; Arason, Adalgeir; Chiquette, Jocelyne; Teixeira, Manuel R.; Olswold, Curtis; Couch, Fergus J.; Lindor, Noralane M.; Wang, Xianshu; Szabo, Csilla I.; Offit, Kenneth; Corines, Marina; Jacobs, Lauren; Robson, Mark E.; Zhang, Liying; Joseph, Vijai; Berger, Andreas; Singer, Christian F.; Rappaport, Christine; Kaulich, Daphne Geschwantler; Pfeiler, Georg; Tea, Muy-Kheng M.; Phelan, Catherine M.; Greene, Mark H.; Mai, Phuong L.; Rennert, Gad; Mulligan, Anna Marie; Glendon, Gord; Tchatchou, Sandrine; Andrulis, Irene L.; Toland, Amanda Ewart; Bojesen, Anders; Pedersen, Inge Sokilde; Thomassen, Mads; Jensen, Uffe Birk; Laitman, Yael; Rantala, Johanna; von Wachenfeldt, Anna; Ehrencrona, Hans; Askmalm, Marie Stenmark; Borg, Åke; Kuchenbaecker, Karoline B.; McGuffog, Lesley; Barrowdale, Daniel; Healey, Sue; Lee, Andrew; Pharoah, Paul D.P.; Chenevix-Trench, Georgia; Antoniou, Antonis C.; Friedman, Eitan

2014-01-01

Background BRCA1 and BRCA2 mutation carriers are at substantially increased risk for developing breast and ovarian cancer. The incomplete penetrance coupled with the variable age at diagnosis in carriers of the same mutation suggests the existence of genetic and non-genetic modifying factors. In this study we evaluated the putative role of variants in many candidate modifier genes. Methods Genotyping data from 15,252 BRCA1 and 8,211 BRCA2 mutation carriers, for known variants (n=3,248) located within or around 445 candidate genes, were available through the iCOGS custom-designed array. Breast and ovarian cancer association analysis was performed within a retrospective cohort approach. Results The observed p-values of association ranged between 0.005-1.000. None of the variants was significantly associated with breast or ovarian cancer risk in either BRCA1 or BRCA2 mutation carriers, after multiple testing adjustments. Conclusion There is little evidence that any of the evaluated candidate variants act as modifiers of breast and/or ovarian cancer risk in BRCA1 or BRCA2 mutation carriers. Impact Genome-wide association studies have been more successful at identifying genetic modifiers of BRCA1/2 penetrance than candidate gene studies. PMID:25336561

A literature search tool for intelligent extraction of disease-associated genes.

PubMed

Jung, Jae-Yoon; DeLuca, Todd F; Nelson, Tristan H; Wall, Dennis P

2014-01-01

To extract disorder-associated genes from the scientific literature in PubMed with greater sensitivity for literature-based support than existing methods. We developed a PubMed query to retrieve disorder-related, original research articles. Then we applied a rule-based text-mining algorithm with keyword matching to extract target disorders, genes with significant results, and the type of study described by the article. We compared our resulting candidate disorder genes and supporting references with existing databases. We demonstrated that our candidate gene set covers nearly all genes in manually curated databases, and that the references supporting the disorder-gene link are more extensive and accurate than other general purpose gene-to-disorder association databases. We implemented a novel publication search tool to find target articles, specifically focused on links between disorders and genotypes. Through comparison against gold-standard manually updated gene-disorder databases and comparison with automated databases of similar functionality we show that our tool can search through the entirety of PubMed to extract the main gene findings for human diseases rapidly and accurately.

Cellular dissection of psoriasis for transcriptome analyses and the post-GWAS era

PubMed Central

2014-01-01

Background Genome-scale studies of psoriasis have been used to identify genes of potential relevance to disease mechanisms. For many identified genes, however, the cell type mediating disease activity is uncertain, which has limited our ability to design gene functional studies based on genomic findings. Methods We identified differentially expressed genes (DEGs) with altered expression in psoriasis lesions (n = 216 patients), as well as candidate genes near susceptibility loci from psoriasis GWAS studies. These gene sets were characterized based upon their expression across 10 cell types present in psoriasis lesions. Susceptibility-associated variation at intergenic (non-coding) loci was evaluated to identify sites of allele-specific transcription factor binding. Results Half of DEGs showed highest expression in skin cells, although the dominant cell type differed between psoriasis-increased DEGs (keratinocytes, 35%) and psoriasis-decreased DEGs (fibroblasts, 33%). In contrast, psoriasis GWAS candidates tended to have highest expression in immune cells (71%), with a significant fraction showing maximal expression in neutrophils (24%, P < 0.001). By identifying candidate cell types for genes near susceptibility loci, we could identify and prioritize SNPs at which susceptibility variants are predicted to influence transcription factor binding. This led to the identification of potentially causal (non-coding) SNPs for which susceptibility variants influence binding of AP-1, NF-κB, IRF1, STAT3 and STAT4. Conclusions These findings underscore the role of innate immunity in psoriasis and highlight neutrophils as a cell type linked with pathogenetic mechanisms. Assignment of candidate cell types to genes emerging from GWAS studies provides a first step towards functional analysis, and we have proposed an approach for generating hypotheses to explain GWAS hits at intergenic loci. PMID:24885462

A data science approach to candidate gene selection of pain regarded as a process of learning and neural plasticity.

PubMed

Ultsch, Alfred; Kringel, Dario; Kalso, Eija; Mogil, Jeffrey S; Lötsch, Jörn

2016-12-01

The increasing availability of "big data" enables novel research approaches to chronic pain while also requiring novel techniques for data mining and knowledge discovery. We used machine learning to combine the knowledge about n = 535 genes identified empirically as relevant to pain with the knowledge about the functions of thousands of genes. Starting from an accepted description of chronic pain as displaying systemic features described by the terms "learning" and "neuronal plasticity," a functional genomics analysis proposed that among the functions of the 535 "pain genes," the biological processes "learning or memory" (P = 8.6 × 10) and "nervous system development" (P = 2.4 × 10) are statistically significantly overrepresented as compared with the annotations to these processes expected by chance. After establishing that the hypothesized biological processes were among important functional genomics features of pain, a subset of n = 34 pain genes were found to be annotated with both Gene Ontology terms. Published empirical evidence supporting their involvement in chronic pain was identified for almost all these genes, including 1 gene identified in March 2016 as being involved in pain. By contrast, such evidence was virtually absent in a randomly selected set of 34 other human genes. Hence, the present computational functional genomics-based method can be used for candidate gene selection, providing an alternative to established methods.

Identifying New Candidate Genes and Chemicals Related to Prostate Cancer Using a Hybrid Network and Shortest Path Approach

PubMed Central

Wang, Meng; Wu, Kai; Lu, Changhong; Kong, Xiangyin

2015-01-01

Prostate cancer is a type of cancer that occurs in the male prostate, a gland in the male reproductive system. Because prostate cancer cells may spread to other parts of the body and can influence human reproduction, understanding the mechanisms underlying this disease is critical for designing effective treatments. The identification of as many genes and chemicals related to prostate cancer as possible will enhance our understanding of this disease. In this study, we proposed a computational method to identify new candidate genes and chemicals based on currently known genes and chemicals related to prostate cancer by applying a shortest path approach in a hybrid network. The hybrid network was constructed according to information concerning chemical-chemical interactions, chemical-protein interactions, and protein-protein interactions. Many of the obtained genes and chemicals are associated with prostate cancer. PMID:26504486

Genome-Wide Association Study Identifying Candidate Genes Influencing Important Agronomic Traits of Flax (Linum usitatissimum L.) Using SLAF-seq

PubMed Central

Xie, Dongwei; Dai, Zhigang; Yang, Zemao; Sun, Jian; Zhao, Debao; Yang, Xue; Zhang, Liguo; Tang, Qing; Su, Jianguang

2018-01-01

Flax (Linum usitatissimum L.) is an important cash crop, and its agronomic traits directly affect yield and quality. Molecular studies on flax remain inadequate because relatively few flax genes have been associated with agronomic traits or have been identified as having potential applications. To identify markers and candidate genes that can potentially be used for genetic improvement of crucial agronomic traits, we examined 224 specimens of core flax germplasm; specifically, phenotypic data for key traits, including plant height, technical length, number of branches, number of fruits, and 1000-grain weight were investigated under three environmental conditions before specific-locus amplified fragment sequencing (SLAF-seq) was employed to perform a genome-wide association study (GWAS) for these five agronomic traits. Subsequently, the results were used to screen single nucleotide polymorphism (SNP) loci and candidate genes that exhibited a significant correlation with the important agronomic traits. Our analyses identified a total of 42 SNP loci that showed significant correlations with the five important agronomic flax traits. Next, candidate genes were screened in the 10 kb zone of each of the 42 SNP loci. These SNP loci were then analyzed by a more stringent screening via co-identification using both a general linear model (GLM) and a mixed linear model (MLM) as well as co-occurrences in at least two of the three environments, whereby 15 final candidate genes were obtained. Based on these results, we determined that UGT and PL are candidate genes for plant height, GRAS and XTH are candidate genes for the number of branches, Contig1437 and LU0019C12 are candidate genes for the number of fruits, and PHO1 is a candidate gene for the 1000-seed weight. We propose that the identified SNP loci and corresponding candidate genes might serve as a biological basis for improving crucial agronomic flax traits. PMID:29375606

Genome-Wide Association Study Identifying Candidate Genes Influencing Important Agronomic Traits of Flax (Linum usitatissimum L.) Using SLAF-seq.

PubMed

Xie, Dongwei; Dai, Zhigang; Yang, Zemao; Sun, Jian; Zhao, Debao; Yang, Xue; Zhang, Liguo; Tang, Qing; Su, Jianguang

2017-01-01

Flax ( Linum usitatissimum L.) is an important cash crop, and its agronomic traits directly affect yield and quality. Molecular studies on flax remain inadequate because relatively few flax genes have been associated with agronomic traits or have been identified as having potential applications. To identify markers and candidate genes that can potentially be used for genetic improvement of crucial agronomic traits, we examined 224 specimens of core flax germplasm; specifically, phenotypic data for key traits, including plant height, technical length, number of branches, number of fruits, and 1000-grain weight were investigated under three environmental conditions before specific-locus amplified fragment sequencing (SLAF-seq) was employed to perform a genome-wide association study (GWAS) for these five agronomic traits. Subsequently, the results were used to screen single nucleotide polymorphism (SNP) loci and candidate genes that exhibited a significant correlation with the important agronomic traits. Our analyses identified a total of 42 SNP loci that showed significant correlations with the five important agronomic flax traits. Next, candidate genes were screened in the 10 kb zone of each of the 42 SNP loci. These SNP loci were then analyzed by a more stringent screening via co-identification using both a general linear model (GLM) and a mixed linear model (MLM) as well as co-occurrences in at least two of the three environments, whereby 15 final candidate genes were obtained. Based on these results, we determined that UGT and PL are candidate genes for plant height, GRAS and XTH are candidate genes for the number of branches, Contig1437 and LU0019C12 are candidate genes for the number of fruits, and PHO1 is a candidate gene for the 1000-seed weight. We propose that the identified SNP loci and corresponding candidate genes might serve as a biological basis for improving crucial agronomic flax traits.

A direct molecular link between the autism candidate gene RORa and the schizophrenia candidate MIR137

NASA Astrophysics Data System (ADS)

Devanna, Paolo; Vernes, Sonja C.

2014-02-01

Retinoic acid-related orphan receptor alpha gene (RORa) and the microRNA MIR137 have both recently been identified as novel candidate genes for neuropsychiatric disorders. RORa encodes a ligand-dependent orphan nuclear receptor that acts as a transcriptional regulator and miR-137 is a brain enriched small non-coding RNA that interacts with gene transcripts to control protein levels. Given the mounting evidence for RORa in autism spectrum disorders (ASD) and MIR137 in schizophrenia and ASD, we investigated if there was a functional biological relationship between these two genes. Herein, we demonstrate that miR-137 targets the 3'UTR of RORa in a site specific manner. We also provide further support for MIR137 as an autism candidate by showing that a large number of previously implicated autism genes are also putatively targeted by miR-137. This work supports the role of MIR137 as an ASD candidate and demonstrates a direct biological link between these previously unrelated autism candidate genes.

Candidate genes and molecular markers associated with heat tolerance in colonial Bentgrass.

PubMed

Jespersen, David; Belanger, Faith C; Huang, Bingru

2017-01-01

Elevated temperature is a major abiotic stress limiting the growth of cool-season grasses during the summer months. The objectives of this study were to determine the genetic variation in the expression patterns of selected genes involved in several major metabolic pathways regulating heat tolerance for two genotypes contrasting in heat tolerance to confirm their status as potential candidate genes, and to identify PCR-based markers associated with candidate genes related to heat tolerance in a colonial (Agrostis capillaris L.) x creeping bentgrass (Agrostis stolonifera L.) hybrid backcross population. Plants were subjected to heat stress in controlled-environmental growth chambers for phenotypic evaluation and determination of genetic variation in candidate gene expression. Molecular markers were developed for genes involved in protein degradation (cysteine protease), antioxidant defense (catalase and glutathione-S-transferase), energy metabolism (glyceraldehyde-3-phosphate dehydrogenase), cell expansion (expansin), and stress protection (heat shock proteins HSP26, HSP70, and HSP101). Kruskal-Wallis analysis, a commonly used non-parametric test used to compare population individuals with or without the gene marker, found the physiological traits of chlorophyll content, electrolyte leakage, normalized difference vegetative index, and turf quality were associated with all candidate gene markers with the exception of HSP101. Differential gene expression was frequently found for the tested candidate genes. The development of candidate gene markers for important heat tolerance genes may allow for the development of new cultivars with increased abiotic stress tolerance using marker-assisted selection.

Candidate genes and molecular markers associated with heat tolerance in colonial Bentgrass

PubMed Central

Jespersen, David; Belanger, Faith C.; Huang, Bingru

2017-01-01

Elevated temperature is a major abiotic stress limiting the growth of cool-season grasses during the summer months. The objectives of this study were to determine the genetic variation in the expression patterns of selected genes involved in several major metabolic pathways regulating heat tolerance for two genotypes contrasting in heat tolerance to confirm their status as potential candidate genes, and to identify PCR-based markers associated with candidate genes related to heat tolerance in a colonial (Agrostis capillaris L.) x creeping bentgrass (Agrostis stolonifera L.) hybrid backcross population. Plants were subjected to heat stress in controlled-environmental growth chambers for phenotypic evaluation and determination of genetic variation in candidate gene expression. Molecular markers were developed for genes involved in protein degradation (cysteine protease), antioxidant defense (catalase and glutathione-S-transferase), energy metabolism (glyceraldehyde-3-phosphate dehydrogenase), cell expansion (expansin), and stress protection (heat shock proteins HSP26, HSP70, and HSP101). Kruskal-Wallis analysis, a commonly used non-parametric test used to compare population individuals with or without the gene marker, found the physiological traits of chlorophyll content, electrolyte leakage, normalized difference vegetative index, and turf quality were associated with all candidate gene markers with the exception of HSP101. Differential gene expression was frequently found for the tested candidate genes. The development of candidate gene markers for important heat tolerance genes may allow for the development of new cultivars with increased abiotic stress tolerance using marker-assisted selection. PMID:28187136

Optimal Reference Genes for Gene Expression Normalization in Trichomonas vaginalis.

PubMed

dos Santos, Odelta; de Vargas Rigo, Graziela; Frasson, Amanda Piccoli; Macedo, Alexandre José; Tasca, Tiana

2015-01-01

Trichomonas vaginalis is the etiologic agent of trichomonosis, the most common non-viral sexually transmitted disease worldwide. This infection is associated with several health consequences, including cervical and prostate cancers and HIV acquisition. Gene expression analysis has been facilitated because of available genome sequences and large-scale transcriptomes in T. vaginalis, particularly using quantitative real-time polymerase chain reaction (qRT-PCR), one of the most used methods for molecular studies. Reference genes for normalization are crucial to ensure the accuracy of this method. However, to the best of our knowledge, a systematic validation of reference genes has not been performed for T. vaginalis. In this study, the transcripts of nine candidate reference genes were quantified using qRT-PCR under different cultivation conditions, and the stability of these genes was compared using the geNorm and NormFinder algorithms. The most stable reference genes were α-tubulin, actin and DNATopII, and, conversely, the widely used T. vaginalis reference genes GAPDH and β-tubulin were less stable. The PFOR gene was used to validate the reliability of the use of these candidate reference genes. As expected, the PFOR gene was upregulated when the trophozoites were cultivated with ferrous ammonium sulfate when the DNATopII, α-tubulin and actin genes were used as normalizing gene. By contrast, the PFOR gene was downregulated when the GAPDH gene was used as an internal control, leading to misinterpretation of the data. These results provide an important starting point for reference gene selection and gene expression analysis with qRT-PCR studies of T. vaginalis.

Optimal Reference Genes for Gene Expression Normalization in Trichomonas vaginalis

PubMed Central

dos Santos, Odelta; de Vargas Rigo, Graziela; Frasson, Amanda Piccoli; Macedo, Alexandre José; Tasca, Tiana

2015-01-01

Trichomonas vaginalis is the etiologic agent of trichomonosis, the most common non-viral sexually transmitted disease worldwide. This infection is associated with several health consequences, including cervical and prostate cancers and HIV acquisition. Gene expression analysis has been facilitated because of available genome sequences and large-scale transcriptomes in T. vaginalis, particularly using quantitative real-time polymerase chain reaction (qRT-PCR), one of the most used methods for molecular studies. Reference genes for normalization are crucial to ensure the accuracy of this method. However, to the best of our knowledge, a systematic validation of reference genes has not been performed for T. vaginalis. In this study, the transcripts of nine candidate reference genes were quantified using qRT-PCR under different cultivation conditions, and the stability of these genes was compared using the geNorm and NormFinder algorithms. The most stable reference genes were α-tubulin, actin and DNATopII, and, conversely, the widely used T. vaginalis reference genes GAPDH and β-tubulin were less stable. The PFOR gene was used to validate the reliability of the use of these candidate reference genes. As expected, the PFOR gene was upregulated when the trophozoites were cultivated with ferrous ammonium sulfate when the DNATopII, α-tubulin and actin genes were used as normalizing gene. By contrast, the PFOR gene was downregulated when the GAPDH gene was used as an internal control, leading to misinterpretation of the data. These results provide an important starting point for reference gene selection and gene expression analysis with qRT-PCR studies of T. vaginalis. PMID:26393928

DISSECTING THE GENETICS OF HUMAN HIGH MYOPIA: A MOLECULAR BIOLOGIC APPROACH

PubMed Central

Young, Terri L

2004-01-01

ABSTRACT Purpose Despite the plethora of experimental myopia animal studies that demonstrate biochemical factor changes in various eye tissues, and limited human studies utilizing pharmacologic agents to thwart axial elongation, we have little knowledge of the basic physiology that drives myopic development. Identifying the implicated genes for myopia susceptibility will provide a fundamental molecular understanding of how myopia occurs and may lead to directed physiologic (ie, pharmacologic, gene therapy) interventions. The purpose of this proposal is to describe the results of positional candidate gene screening of selected genes within the autosomal dominant high-grade myopia-2 locus (MYP2) on chromosome 18p11.31. Methods A physical map of a contracted MYP2 interval was compiled, and gene expression studies in ocular tissues using complementary DNA library screens, microarray matches, and reverse-transcription techniques aided in prioritizing gene selection for screening. The TGIF, EMLIN-2, MLCB, and CLUL1 genes were screened in DNA samples from unrelated controls and in high-myopia affected and unaffected family members from the original seven MYP2 pedigrees. All candidate genes were screened by direct base pair sequence analysis. Results Consistent segregation of a gene sequence alteration (polymorphism) with myopia was not demonstrated in any of the seven families. Novel single nucleotide polymorphisms were found. Conclusion The positional candidate genes TGIF, EMLIN-2, MLCB, and CLUL1 are not associated with MYP2-linked high-grade myopia. Base change polymorphisms discovered with base sequence screening of these genes were submitted to an Internet database. Other genes that also map within the interval are currently undergoing mutation screening. PMID:15747770

Exploring candidate biomarkers for lung and prostate cancers using gene expression and flux variability analysis.

PubMed

Asgari, Yazdan; Khosravi, Pegah; Zabihinpour, Zahra; Habibi, Mahnaz

2018-02-19

Genome-scale metabolic models have provided valuable resources for exploring changes in metabolism under normal and cancer conditions. However, metabolism itself is strongly linked to gene expression, so integration of gene expression data into metabolic models might improve the detection of genes involved in the control of tumor progression. Herein, we considered gene expression data as extra constraints to enhance the predictive powers of metabolic models. We reconstructed genome-scale metabolic models for lung and prostate, under normal and cancer conditions to detect the major genes associated with critical subsystems during tumor development. Furthermore, we utilized gene expression data in combination with an information theory-based approach to reconstruct co-expression networks of the human lung and prostate in both cohorts. Our results revealed 19 genes as candidate biomarkers for lung and prostate cancer cells. This study also revealed that the development of a complementary approach (integration of gene expression and metabolic profiles) could lead to proposing novel biomarkers and suggesting renovated cancer treatment strategies which have not been possible to detect using either of the methods alone.

A small number of candidate gene SNPs reveal continental ancestry in African Americans

PubMed Central

KODAMAN, NURI; ALDRICH, MELINDA C.; SMITH, JEFFREY R.; SIGNORELLO, LISA B.; BRADLEY, KEVIN; BREYER, JOAN; COHEN, SARAH S.; LONG, JIRONG; CAI, QIUYIN; GILES, JUSTIN; BUSH, WILLIAM S.; BLOT, WILLIAM J.; MATTHEWS, CHARLES E.; WILLIAMS, SCOTT M.

2013-01-01

SUMMARY Using genetic data from an obesity candidate gene study of self-reported African Americans and European Americans, we investigated the number of Ancestry Informative Markers (AIMs) and candidate gene SNPs necessary to infer continental ancestry. Proportions of African and European ancestry were assessed with STRUCTURE (K=2), using 276 AIMs. These reference values were compared to estimates derived using 120, 60, 30, and 15 SNP subsets randomly chosen from the 276 AIMs and from 1144 SNPs in 44 candidate genes. All subsets generated estimates of ancestry consistent with the reference estimates, with mean correlations greater than 0.99 for all subsets of AIMs, and mean correlations of 0.99±0.003; 0.98± 0.01; 0.93±0.03; and 0.81± 0.11 for subsets of 120, 60, 30, and 15 candidate gene SNPs, respectively. Among African Americans, the median absolute difference from reference African ancestry values ranged from 0.01 to 0.03 for the four AIMs subsets and from 0.03 to 0.09 for the four candidate gene SNP subsets. Furthermore, YRI/CEU Fst values provided a metric to predict the performance of candidate gene SNPs. Our results demonstrate that a small number of SNPs randomly selected from candidate genes can be used to estimate admixture proportions in African Americans reliably. PMID:23278390

Identification of essential genes and synthetic lethal gene combinations in Escherichia coli K-12.

PubMed

Mori, Hirotada; Baba, Tomoya; Yokoyama, Katsushi; Takeuchi, Rikiya; Nomura, Wataru; Makishi, Kazuichi; Otsuka, Yuta; Dose, Hitomi; Wanner, Barry L

2015-01-01

Here we describe the systematic identification of single genes and gene pairs, whose knockout causes lethality in Escherichia coli K-12. During construction of precise single-gene knockout library of E. coli K-12, we identified 328 essential gene candidates for growth in complex (LB) medium. Upon establishment of the Keio single-gene deletion library, we undertook the development of the ASKA single-gene deletion library carrying a different antibiotic resistance. In addition, we developed tools for identification of synthetic lethal gene combinations by systematic construction of double-gene knockout mutants. We introduce these methods herein.

A gene-signature progression approach to identifying candidate small-molecule cancer therapeutics with connectivity mapping.

PubMed

Wen, Qing; Kim, Chang-Sik; Hamilton, Peter W; Zhang, Shu-Dong

2016-05-11

Gene expression connectivity mapping has gained much popularity recently with a number of successful applications in biomedical research testifying its utility and promise. Previously methodological research in connectivity mapping mainly focused on two of the key components in the framework, namely, the reference gene expression profiles and the connectivity mapping algorithms. The other key component in this framework, the query gene signature, has been left to users to construct without much consensus on how this should be done, albeit it has been an issue most relevant to end users. As a key input to the connectivity mapping process, gene signature is crucially important in returning biologically meaningful and relevant results. This paper intends to formulate a standardized procedure for constructing high quality gene signatures from a user's perspective. We describe a two-stage process for making quality gene signatures using gene expression data as initial inputs. First, a differential gene expression analysis comparing two distinct biological states; only the genes that have passed stringent statistical criteria are considered in the second stage of the process, which involves ranking genes based on statistical as well as biological significance. We introduce a "gene signature progression" method as a standard procedure in connectivity mapping. Starting from the highest ranked gene, we progressively determine the minimum length of the gene signature that allows connections to the reference profiles (drugs) being established with a preset target false discovery rate. We use a lung cancer dataset and a breast cancer dataset as two case studies to demonstrate how this standardized procedure works, and we show that highly relevant and interesting biological connections are returned. Of particular note is gefitinib, identified as among the candidate therapeutics in our lung cancer case study. Our gene signature was based on gene expression data from Taiwan female non-smoker lung cancer patients, while there is evidence from independent studies that gefitinib is highly effective in treating women, non-smoker or former light smoker, advanced non-small cell lung cancer patients of Asian origin. In summary, we introduced a gene signature progression method into connectivity mapping, which enables a standardized procedure for constructing high quality gene signatures. This progression method is particularly useful when the number of differentially expressed genes identified is large, and when there is a need to prioritize them to be included in the query signature. The results from two case studies demonstrate that the approach we have developed is capable of obtaining pertinent candidate drugs with high precision.

Machine Learning–Based Differential Network Analysis: A Study of Stress-Responsive Transcriptomes in Arabidopsis[W

PubMed Central

Ma, Chuang; Xin, Mingming; Feldmann, Kenneth A.; Wang, Xiangfeng

2014-01-01

Machine learning (ML) is an intelligent data mining technique that builds a prediction model based on the learning of prior knowledge to recognize patterns in large-scale data sets. We present an ML-based methodology for transcriptome analysis via comparison of gene coexpression networks, implemented as an R package called machine learning–based differential network analysis (mlDNA) and apply this method to reanalyze a set of abiotic stress expression data in Arabidopsis thaliana. The mlDNA first used a ML-based filtering process to remove nonexpressed, constitutively expressed, or non-stress-responsive “noninformative” genes prior to network construction, through learning the patterns of 32 expression characteristics of known stress-related genes. The retained “informative” genes were subsequently analyzed by ML-based network comparison to predict candidate stress-related genes showing expression and network differences between control and stress networks, based on 33 network topological characteristics. Comparative evaluation of the network-centric and gene-centric analytic methods showed that mlDNA substantially outperformed traditional statistical testing–based differential expression analysis at identifying stress-related genes, with markedly improved prediction accuracy. To experimentally validate the mlDNA predictions, we selected 89 candidates out of the 1784 predicted salt stress–related genes with available SALK T-DNA mutagenesis lines for phenotypic screening and identified two previously unreported genes, mutants of which showed salt-sensitive phenotypes. PMID:24520154

EnRICH: Extraction and Ranking using Integration and Criteria Heuristics.

PubMed

Zhang, Xia; Greenlee, M Heather West; Serb, Jeanne M

2013-01-15

High throughput screening technologies enable biologists to generate candidate genes at a rate that, due to time and cost constraints, cannot be studied by experimental approaches in the laboratory. Thus, it has become increasingly important to prioritize candidate genes for experiments. To accomplish this, researchers need to apply selection requirements based on their knowledge, which necessitates qualitative integration of heterogeneous data sources and filtration using multiple criteria. A similar approach can also be applied to putative candidate gene relationships. While automation can assist in this routine and imperative procedure, flexibility of data sources and criteria must not be sacrificed. A tool that can optimize the trade-off between automation and flexibility to simultaneously filter and qualitatively integrate data is needed to prioritize candidate genes and generate composite networks from heterogeneous data sources. We developed the java application, EnRICH (Extraction and Ranking using Integration and Criteria Heuristics), in order to alleviate this need. Here we present a case study in which we used EnRICH to integrate and filter multiple candidate gene lists in order to identify potential retinal disease genes. As a result of this procedure, a candidate pool of several hundred genes was narrowed down to five candidate genes, of which four are confirmed retinal disease genes and one is associated with a retinal disease state. We developed a platform-independent tool that is able to qualitatively integrate multiple heterogeneous datasets and use different selection criteria to filter each of them, provided the datasets are tables that have distinct identifiers (required) and attributes (optional). With the flexibility to specify data sources and filtering criteria, EnRICH automatically prioritizes candidate genes or gene relationships for biologists based on their specific requirements. Here, we also demonstrate that this tool can be effectively and easily used to apply highly specific user-defined criteria and can efficiently identify high quality candidate genes from relatively sparse datasets.

Common genetic variants related to genomic integrity and risk of papillary thyroid cancer

PubMed Central

Neta, Gila; Brenner, Alina V.; Sturgis, Erich M.; Pfeiffer, Ruth M.; Hutchinson, Amy A.; Aschebrook-Kilfoy, Briseis; Yeager, Meredith; Xu, Li; Wheeler, William; Abend, Michael; Ron, Elaine; Tucker, Margaret A.; Chanock, Stephen J.; Sigurdson, Alice J.

2011-01-01

DNA damage is an important mechanism in carcinogenesis, so genes related to maintaining genomic integrity may influence papillary thyroid cancer (PTC) risk. Candidate gene studies targeting some of these genes have identified only a few polymorphisms associated with risk of PTC. Here, we expanded the scope of previous candidate studies by increasing the number and coverage of genes related to maintenance of genomic integrity. We evaluated 5077 tag single-nucleotide polymorphisms (SNPs) from 340 candidate gene regions hypothesized to be involved in DNA repair, epigenetics, tumor suppression, apoptosis, telomere function and cell cycle control and signaling pathways in a case–control study of 344 PTC cases and 452 matched controls. We estimated odds ratios for associations of single SNPs with PTC risk and combined P values for SNPs in the same gene region or pathway to obtain gene region-specific or pathway-specific P values using adaptive rank-truncated product methods. Nine SNPs had P values <0.0005, three of which were in HDAC4 and were inversely related to PTC risk. After multiple comparisons adjustment, no SNPs remained associated with PTC risk. Seven gene regions were associated with PTC risk at P < 0.01, including HUS1, ALKBH3, HDAC4, BAK1, FAF1_CDKN2C, DACT3 and FZD6. Our results suggest a possible role of genes involved in maintenance of genomic integrity in relation to risk of PTC. PMID:21642358

Reconstructing directed gene regulatory network by only gene expression data.

PubMed

Zhang, Lu; Feng, Xi Kang; Ng, Yen Kaow; Li, Shuai Cheng

2016-08-18

Accurately identifying gene regulatory network is an important task in understanding in vivo biological activities. The inference of such networks is often accomplished through the use of gene expression data. Many methods have been developed to evaluate gene expression dependencies between transcription factor and its target genes, and some methods also eliminate transitive interactions. The regulatory (or edge) direction is undetermined if the target gene is also a transcription factor. Some methods predict the regulatory directions in the gene regulatory networks by locating the eQTL single nucleotide polymorphism, or by observing the gene expression changes when knocking out/down the candidate transcript factors; regrettably, these additional data are usually unavailable, especially for the samples deriving from human tissues. In this study, we propose the Context Based Dependency Network (CBDN), a method that is able to infer gene regulatory networks with the regulatory directions from gene expression data only. To determine the regulatory direction, CBDN computes the influence of source to target by evaluating the magnitude changes of expression dependencies between the target gene and the others with conditioning on the source gene. CBDN extends the data processing inequality by involving the dependency direction to distinguish between direct and transitive relationship between genes. We also define two types of important regulators which can influence a majority of the genes in the network directly or indirectly. CBDN can detect both of these two types of important regulators by averaging the influence functions of candidate regulator to the other genes. In our experiments with simulated and real data, even with the regulatory direction taken into account, CBDN outperforms the state-of-the-art approaches for inferring gene regulatory network. CBDN identifies the important regulators in the predicted network: 1. TYROBP influences a batch of genes that are related to Alzheimer's disease; 2. ZNF329 and RB1 significantly regulate those 'mesenchymal' gene expression signature genes for brain tumors. By merely leveraging gene expression data, CBDN can efficiently infer the existence of gene-gene interactions as well as their regulatory directions. The constructed networks are helpful in the identification of important regulators for complex diseases.

Search for sarcoidosis candidate genes by integration of data from genomic, transcriptomic and proteomic studies.

PubMed

Maver, Ales; Medica, Igor; Peterlin, Borut

2009-12-01

The search for gene candidates in multifactorial diseases such as sarcoidosis can be based on the integration of linkage association data, gene expression data, and protein profile data from genomic, transcriptomic and proteomic studies, respectively. In this study we performed a literature-based search for studies reporting such data, followed by integration of collected information. Different databases were examined--Medline, HugGE Navigator, ArrayExpress and Gene Expression Omnibus (GEO). Candidate genes were defined as genes which were reported in at least 2 different types of omics studies. Genes previously investigated in sarcoidosis were excluded from further analyses. We identified 177 genes associated with sarcoidosis as potential new candidate genes. Subsequently, 9 gene candidates identified to overlap in 2 different types of studies (genomic, transcriptomic and/or proteomic) were consistently reported in at least 3 studies: SERPINB1, FABP4, S100A8, HBEGF, IL7R, LRIG1, PTPN23, DPM2 and NUP214. These genes are involved in regulation of immune response, cellular proliferation, apoptosis, inhibition of protease activity, lipid metabolism. Exact biological functions of HBEGF, LRIG1, PTPN23, DPM2 and NUP214 remain to be completely elucidated. We propose 9 candidate genes: SERPINB1, FABP4, S100A8, HBEGF, IL7R, LRIG1, PTPN23, DPM2 and NUP214, as genes with high potential for association with sarcoidosis.

An assessment of heavy ion irradiation mutagenesis for reverse genetics in wheat (Triticum aestivum L.).

PubMed

Fitzgerald, Timothy L; Powell, Jonathan J; Stiller, Jiri; Weese, Terri L; Abe, Tomoko; Zhao, Guangyao; Jia, Jizeng; McIntyre, C Lynne; Li, Zhongyi; Manners, John M; Kazan, Kemal

2015-01-01

Reverse genetic techniques harnessing mutational approaches are powerful tools that can provide substantial insight into gene function in plants. However, as compared to diploid species, reverse genetic analyses in polyploid plants such as bread wheat can present substantial challenges associated with high levels of sequence and functional similarity amongst homoeologous loci. We previously developed a high-throughput method to identify deletions of genes within a physically mutagenized wheat population. Here we describe our efforts to combine multiple homoeologous deletions of three candidate disease susceptibility genes (TaWRKY11, TaPFT1 and TaPLDß1). We were able to produce lines featuring homozygous deletions at two of the three homoeoloci for all genes, but this was dependent on the individual mutants used in crossing. Intriguingly, despite extensive efforts, viable lines possessing homozygous deletions at all three homoeoloci could not be produced for any of the candidate genes. To investigate deletion size as a possible reason for this phenomenon, we developed an amplicon sequencing approach based on synteny to Brachypodium distachyon to assess the size of the deletions removing one candidate gene (TaPFT1) in our mutants. These analyses revealed that genomic deletions removing the locus are relatively large, resulting in the loss of multiple additional genes. The implications of this work for the use of heavy ion mutagenesis for reverse genetic analyses in wheat are discussed.

An Assessment of Heavy Ion Irradiation Mutagenesis for Reverse Genetics in Wheat (Triticum aestivum L.)

PubMed Central

Fitzgerald, Timothy L.; Powell, Jonathan J.; Stiller, Jiri; Weese, Terri L.; Abe, Tomoko; Zhao, Guangyao; Jia, Jizeng; McIntyre, C. Lynne; Li, Zhongyi; Manners, John M.; Kazan, Kemal

2015-01-01

Reverse genetic techniques harnessing mutational approaches are powerful tools that can provide substantial insight into gene function in plants. However, as compared to diploid species, reverse genetic analyses in polyploid plants such as bread wheat can present substantial challenges associated with high levels of sequence and functional similarity amongst homoeologous loci. We previously developed a high-throughput method to identify deletions of genes within a physically mutagenized wheat population. Here we describe our efforts to combine multiple homoeologous deletions of three candidate disease susceptibility genes (TaWRKY11, TaPFT1 and TaPLDß1). We were able to produce lines featuring homozygous deletions at two of the three homoeoloci for all genes, but this was dependent on the individual mutants used in crossing. Intriguingly, despite extensive efforts, viable lines possessing homozygous deletions at all three homoeoloci could not be produced for any of the candidate genes. To investigate deletion size as a possible reason for this phenomenon, we developed an amplicon sequencing approach based on synteny to Brachypodium distachyon to assess the size of the deletions removing one candidate gene (TaPFT1) in our mutants. These analyses revealed that genomic deletions removing the locus are relatively large, resulting in the loss of multiple additional genes. The implications of this work for the use of heavy ion mutagenesis for reverse genetic analyses in wheat are discussed. PMID:25719507

Ontology based molecular signatures for immune cell types via gene expression analysis

PubMed Central

2013-01-01

Background New technologies are focusing on characterizing cell types to better understand their heterogeneity. With large volumes of cellular data being generated, innovative methods are needed to structure the resulting data analyses. Here, we describe an ‘Ontologically BAsed Molecular Signature’ (OBAMS) method that identifies novel cellular biomarkers and infers biological functions as characteristics of particular cell types. This method finds molecular signatures for immune cell types based on mapping biological samples to the Cell Ontology (CL) and navigating the space of all possible pairwise comparisons between cell types to find genes whose expression is core to a particular cell type’s identity. Results We illustrate this ontological approach by evaluating expression data available from the Immunological Genome project (IGP) to identify unique biomarkers of mature B cell subtypes. We find that using OBAMS, candidate biomarkers can be identified at every strata of cellular identity from broad classifications to very granular. Furthermore, we show that Gene Ontology can be used to cluster cell types by shared biological processes in order to find candidate genes responsible for somatic hypermutation in germinal center B cells. Moreover, through in silico experiments based on this approach, we have identified genes sets that represent genes overexpressed in germinal center B cells and identify genes uniquely expressed in these B cells compared to other B cell types. Conclusions This work demonstrates the utility of incorporating structured ontological knowledge into biological data analysis – providing a new method for defining novel biomarkers and providing an opportunity for new biological insights. PMID:24004649

Non-coding cancer driver candidates identified with a sample- and position-specific model of the somatic mutation rate

PubMed Central

Juul, Malene; Bertl, Johanna; Guo, Qianyun; Nielsen, Morten Muhlig; Świtnicki, Michał; Hornshøj, Henrik; Madsen, Tobias; Hobolth, Asger; Pedersen, Jakob Skou

2017-01-01

Non-coding mutations may drive cancer development. Statistical detection of non-coding driver regions is challenged by a varying mutation rate and uncertainty of functional impact. Here, we develop a statistically founded non-coding driver-detection method, ncdDetect, which includes sample-specific mutational signatures, long-range mutation rate variation, and position-specific impact measures. Using ncdDetect, we screened non-coding regulatory regions of protein-coding genes across a pan-cancer set of whole-genomes (n = 505), which top-ranked known drivers and identified new candidates. For individual candidates, presence of non-coding mutations associates with altered expression or decreased patient survival across an independent pan-cancer sample set (n = 5454). This includes an antigen-presenting gene (CD1A), where 5’UTR mutations correlate significantly with decreased survival in melanoma. Additionally, mutations in a base-excision-repair gene (SMUG1) correlate with a C-to-T mutational-signature. Overall, we find that a rich model of mutational heterogeneity facilitates non-coding driver identification and integrative analysis points to candidates of potential clinical relevance. DOI: http://dx.doi.org/10.7554/eLife.21778.001 PMID:28362259

Robust and Comprehensive Analysis of 20 Osteoporosis Candidate Genes by Very High-Density Single-Nucleotide Polymorphism Screen Among 405 White Nuclear Families Identified Significant Association and Gene–Gene Interaction

PubMed Central

Xiong, Dong-Hai; Shen, Hui; Zhao, Lan-Juan; Xiao, Peng; Yang, Tie-Lin; Guo, Yan; Wang, Wei; Guo, Yan-Fang; Liu, Yong-Jun; Recker, Robert R; Deng, Hong-Wen

2007-01-01

Many “novel” osteoporosis candidate genes have been proposed in recent years. To advance our knowledge of their roles in osteoporosis, we screened 20 such genes using a set of high-density SNPs in a large family-based study. Our efforts led to the prioritization of those osteoporosis genes and the detection of gene–gene interactions. Introduction We performed large-scale family-based association analyses of 20 novel osteoporosis candidate genes using 277 single nucleotide polymorphisms (SNPs) for the quantitative trait BMD variation and the qualitative trait osteoporosis (OP) at three clinically important skeletal sites: spine, hip, and ultradistal radius (UD). Materials and Methods One thousand eight hundred seventy-three subjects from 405 white nuclear families were genotyped and analyzed with an average density of one SNP per 4 kb across the 20 genes. We conducted association analyses by SNP- and haplotype-based family-based association test (FBAT) and performed gene–gene interaction analyses using multianalytic approaches such as multifactor-dimensionality reduction (MDR) and conditional logistic regression. Results and Conclusions We detected four genes (DBP, LRP5, CYP17, and RANK) that showed highly suggestive associations (10,000-permutation derived empirical global p ≤ 0.01) with spine BMD/OP; four genes (CYP19, RANK, RANKL, and CYP17) highly suggestive for hip BMD/OP; and four genes (CYP19, BMP2, RANK, and TNFR2) highly suggestive for UD BMD/OP. The associations between BMP2 with UD BMD and those between RANK with OP at the spine, hip, and UD also met the experiment-wide stringent criterion (empirical global p ≤ 0.0007). Sex-stratified analyses further showed that some of the significant associations in the total sample were driven by either male or female subjects. In addition, we identified and validated a two-locus gene–gene interaction model involving GCR and ESR2, for which prior biological evidence exists. Our results suggested the prioritization of osteoporosis candidate genes from among the many proposed in recent years and revealed the significant gene–gene interaction effects influencing osteoporosis risk. PMID:17002564

LOD score exclusion analyses for candidate QTLs using random population samples.

PubMed

Deng, Hong-Wen

2003-11-01

While extensive analyses have been conducted to test for, no formal analyses have been conducted to test against, the importance of candidate genes as putative QTLs using random population samples. Previously, we developed an LOD score exclusion mapping approach for candidate genes for complex diseases. Here, we extend this LOD score approach for exclusion analyses of candidate genes for quantitative traits. Under this approach, specific genetic effects (as reflected by heritability) and inheritance models at candidate QTLs can be analyzed and if an LOD score is < or = -2.0, the locus can be excluded from having a heritability larger than that specified. Simulations show that this approach has high power to exclude a candidate gene from having moderate genetic effects if it is not a QTL and is robust to population admixture. Our exclusion analysis complements association analysis for candidate genes as putative QTLs in random population samples. The approach is applied to test the importance of Vitamin D receptor (VDR) gene as a potential QTL underlying the variation of bone mass, an important determinant of osteoporosis.

Genetic Influences on Conduct Disorder

PubMed Central

Salvatore, Jessica E.; Dick, Danielle M.

2016-01-01

Conduct disorder (CD) is a moderately heritable psychiatric disorder of childhood and adolescence characterized by aggression toward people and animals, destruction of property, deceitfulness or theft, and serious violation of rules. Genome-wide scans using linkage and association methods have identified a number of suggestive genomic regions that are pending replication. A small number of candidate genes (e.g., GABRA2, MAOA, SLC6A4, AVPR1A) are associated with CD related phenotypes across independent studies; however, failures to replicate also exist. Studies of gene-environment interplay show that CD genetic predispositions also contribute to selection into higher-risk environments, and that environmental factors can alter the importance of CD genetic factors and differentially methylate CD candidate genes. The field’s understanding of CD etiology will benefit from larger, adequately powered studies in gene identification efforts; the incorporation of polygenic approaches in gene-environment interplay studies; attention to the mechanisms of risk from genes to brain to behavior; and the use of genetically informative data to test quasi-causal hypotheses about purported risk factors. PMID:27350097

Association of candidate genes with drought tolerance traits in diverse perennial ryegrass accessions

Treesearch

Xiaoqing Yu; Guihua Bai; Shuwei Liu; Na Luo; Ying Wang; Douglas S. Richmond; Paula M. Pijut; Scott A. Jackson; Jianming Yu; Yiwei Jiang

2013-01-01

Drought is a major environmental stress limiting growth of perennial grasses in temperate regions. Plant drought tolerance is a complex trait that is controlled by multiple genes. Candidate gene association mapping provides a powerful tool for dissection of complex traits. Candidate gene association mapping of drought tolerance traits was conducted in 192 diverse...

SNP discovery in candidate adaptive genes using exon capture in a free-ranging alpine ungulate

USGS Publications Warehouse

Roffler, Gretchen H.; Amish, Stephen J.; Smith, Seth; Cosart, Ted F.; Kardos, Marty; Schwartz, Michael K.; Luikart, Gordon

2016-01-01

Identification of genes underlying genomic signatures of natural selection is key to understanding adaptation to local conditions. We used targeted resequencing to identify SNP markers in 5321 candidate adaptive genes associated with known immunological, metabolic and growth functions in ovids and other ungulates. We selectively targeted 8161 exons in protein-coding and nearby 5′ and 3′ untranslated regions of chosen candidate genes. Targeted sequences were taken from bighorn sheep (Ovis canadensis) exon capture data and directly from the domestic sheep genome (Ovis aries v. 3; oviAri3). The bighorn sheep sequences used in the Dall's sheep (Ovis dalli dalli) exon capture aligned to 2350 genes on the oviAri3 genome with an average of 2 exons each. We developed a microfluidic qPCR-based SNP chip to genotype 476 Dall's sheep from locations across their range and test for patterns of selection. Using multiple corroborating approaches (lositan and bayescan), we detected 28 SNP loci potentially under selection. We additionally identified candidate loci significantly associated with latitude, longitude, precipitation and temperature, suggesting local environmental adaptation. The three methods demonstrated consistent support for natural selection on nine genes with immune and disease-regulating functions (e.g. Ovar-DRA, APC, BATF2, MAGEB18), cell regulation signalling pathways (e.g. KRIT1, PI3K, ORRC3), and respiratory health (CYSLTR1). Characterizing adaptive allele distributions from novel genetic techniques will facilitate investigation of the influence of environmental variation on local adaptation of a northern alpine ungulate throughout its range. This research demonstrated the utility of exon capture for gene-targeted SNP discovery and subsequent SNP chip genotyping using low-quality samples in a nonmodel species.

Possible ancestral structure in human populations.

PubMed

Plagnol, Vincent; Wall, Jeffrey D

2006-07-01

Determining the evolutionary relationships between fossil hominid groups such as Neanderthals and modern humans has been a question of enduring interest in human evolutionary genetics. Here we present a new method for addressing whether archaic human groups contributed to the modern gene pool (called ancient admixture), using the patterns of variation in contemporary human populations. Our method improves on previous work by explicitly accounting for recent population history before performing the analyses. Using sequence data from the Environmental Genome Project, we find strong evidence for ancient admixture in both a European and a West African population (p approximately 10(-7)), with contributions to the modern gene pool of at least 5%. While Neanderthals form an obvious archaic source population candidate in Europe, there is not yet a clear source population candidate in West Africa.

Convergence of genome-wide association and candidate gene studies for alcoholism.

PubMed

Olfson, Emily; Bierut, Laura Jean

2012-12-01

Genome-wide association (GWA) studies have led to a paradigm shift in how researchers study the genetics underlying disease. Many GWA studies are now publicly available and can be used to examine whether or not previously proposed candidate genes are supported by GWA data. This approach is particularly important for the field of alcoholism because the contribution of many candidate genes remains controversial. Using the Human Genome Epidemiology (HuGE) Navigator, we selected candidate genes for alcoholism that have been frequently examined in scientific articles in the past decade. Specific candidate loci as well as all the reported single nucleotide polymorphisms (SNPs) in candidate genes were examined in the Study of Addiction: Genetics and Environment (SAGE), a GWA study comparing alcohol-dependent and nondependent subjects. Several commonly reported candidate loci, including rs1800497 in DRD2, rs698 in ADH1C, rs1799971 in OPRM1, and rs4680 in COMT, are not replicated in SAGE (p > 0.05). Among candidate loci available for analysis, only rs279858 in GABRA2 (p = 0.0052, OR = 1.16) demonstrated a modest association. Examination of all SNPs reported in SAGE in over 50 candidate genes revealed no SNPs with large frequency differences between cases and controls, and the lowest p-value of any SNP was 0.0006. We provide evidence that several extensively studied candidate loci do not have a strong contribution to risk of developing alcohol dependence in European and African ancestry populations. Owing to the lack of coverage, we were unable to rule out the contribution of other variants, and these genes and particular loci warrant further investigation. Our analysis demonstrates that publicly available GWA results can be used to better understand which if any of previously proposed candidate genes contribute to disease. Furthermore, we illustrate how examining the convergence of candidate gene and GWA studies can help elucidate the genetic architecture of alcoholism and more generally complex diseases. Copyright © 2012 by the Research Society on Alcoholism.

Selection of appropriate reference genes for the detection of rhythmic gene expression via quantitative real-time PCR in Tibetan hulless barley.

PubMed

Cai, Jing; Li, Pengfei; Luo, Xiao; Chang, Tianliang; Li, Jiaxing; Zhao, Yuwei; Xu, Yao

2018-01-01

Hulless barley (Hordeum vulgare L. var. nudum. hook. f.) has been cultivated as a major crop in the Qinghai-Tibet plateau of China for thousands of years. Compared to other cereal crops, the Tibetan hulless barley has developed stronger endogenous resistances to survive in the severe environment of its habitat. To understand the unique resistant mechanisms of this plant, detailed genetic studies need to be performed. The quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR) is the most commonly used method in detecting gene expression. However, the selection of stable reference genes under limited experimental conditions was considered to be an essential step for obtaining accurate results in qRT-PCR. In this study, 10 candidate reference genes-ACT (Actin), E2 (Ubiquitin conjugating enzyme 2), TUBα (Alpha-tubulin), TUBβ6 (Beta-tubulin 6), GAPDH (Glyceraldehyde 3-phosphate dehydrogenase), EF-1α (Elongation factor 1-alpha), SAMDC (S-adenosylmethionine decarboxylase), PKABA1 (Gene for protein kinase HvPKABA1), PGK (Phosphoglycerate kinase), and HSP90 (Heat shock protein 90)-were selected from the NCBI gene database of barley. Following qRT-PCR amplifications of all candidate reference genes in Tibetan hulless barley seedlings under various stressed conditions, the stabilities of these candidates were analyzed by three individual software packages including geNorm, NormFinder, and BestKeeper. The results demonstrated that TUBβ6, E2, TUBα, and HSP90 were generally the most suitable sets under all tested conditions; similarly, TUBα and HSP90 showed peak stability under salt stress, TUBα and EF-1α were the most suitable reference genes under cold stress, and ACT and E2 were the most stable under drought stress. Finally, a known circadian gene CCA1 was used to verify the service ability of chosen reference genes. The results confirmed that all recommended reference genes by the three software were suitable for gene expression analysis under tested stress conditions by the qRT-PCR method.

Defining the human macula transcriptome and candidate retinal disease genes using EyeSAGE.

PubMed

Bowes Rickman, Catherine; Ebright, Jessica N; Zavodni, Zachary J; Yu, Ling; Wang, Tianyuan; Daiger, Stephen P; Wistow, Graeme; Boon, Kathy; Hauser, Michael A

2006-06-01

To develop large-scale, high-throughput annotation of the human macula transcriptome and to identify and prioritize candidate genes for inherited retinal dystrophies, based on ocular-expression profiles using serial analysis of gene expression (SAGE). Two human retina and two retinal pigment epithelium (RPE)/choroid SAGE libraries made from matched macula or midperipheral retina and adjacent RPE/choroid of morphologically normal 28- to 66-year-old donors and a human central retina longSAGE library made from 41- to 66-year-old donors were generated. Their transcription profiles were entered into a relational database, EyeSAGE, including microarray expression profiles of retina and publicly available normal human tissue SAGE libraries. EyeSAGE was used to identify retina- and RPE-specific and -associated genes, and candidate genes for retina and RPE disease loci. Differential and/or cell-type specific expression was validated by quantitative and single-cell RT-PCR. Cone photoreceptor-associated gene expression was elevated in the macula transcription profiles. Analysis of the longSAGE retina tags enhanced tag-to-gene mapping and revealed alternatively spliced genes. Analysis of candidate gene expression tables for the identified Bardet-Biedl syndrome disease gene (BBS5) in the BBS5 disease region table yielded BBS5 as the top candidate. Compelling candidates for inherited retina diseases were identified. The EyeSAGE database, combining three different gene-profiling platforms including the authors' multidonor-derived retina/RPE SAGE libraries and existing single-donor retina/RPE libraries, is a powerful resource for definition of the retina and RPE transcriptomes. It can be used to identify retina-specific genes, including alternatively spliced transcripts and to prioritize candidate genes within mapped retinal disease regions.

Composite selection signals can localize the trait specific genomic regions in multi-breed populations of cattle and sheep

PubMed Central

2014-01-01

Background Discerning the traits evolving under neutral conditions from those traits evolving rapidly because of various selection pressures is a great challenge. We propose a new method, composite selection signals (CSS), which unifies the multiple pieces of selection evidence from the rank distribution of its diverse constituent tests. The extreme CSS scores capture highly differentiated loci and underlying common variants hauling excess haplotype homozygosity in the samples of a target population. Results The data on high-density genotypes were analyzed for evidence of an association with either polledness or double muscling in various cohorts of cattle and sheep. In cattle, extreme CSS scores were found in the candidate regions on autosome BTA-1 and BTA-2, flanking the POLL locus and MSTN gene, for polledness and double muscling, respectively. In sheep, the regions with extreme scores were localized on autosome OAR-2 harbouring the MSTN gene for double muscling and on OAR-10 harbouring the RXFP2 gene for polledness. In comparison to the constituent tests, there was a partial agreement between the signals at the four candidate loci; however, they consistently identified additional genomic regions harbouring no known genes. Persuasively, our list of all the additional significant CSS regions contains genes that have been successfully implicated to secondary phenotypic diversity among several subpopulations in our data. For example, the method identified a strong selection signature for stature in cattle capturing selective sweeps harbouring UQCC-GDF5 and PLAG1-CHCHD7 gene regions on BTA-13 and BTA-14, respectively. Both gene pairs have been previously associated with height in humans, while PLAG1-CHCHD7 has also been reported for stature in cattle. In the additional analysis, CSS identified significant regions harbouring multiple genes for various traits under selection in European cattle including polledness, adaptation, metabolism, growth rate, stature, immunity, reproduction traits and some other candidate genes for dairy and beef production. Conclusions CSS successfully localized the candidate regions in validation datasets as well as identified previously known and novel regions for various traits experiencing selection pressure. Together, the results demonstrate the utility of CSS by its improved power, reduced false positives and high-resolution of selection signals as compared to individual constituent tests. PMID:24636660

Network-based analysis of differentially expressed genes in cerebrospinal fluid (CSF) and blood reveals new candidate genes for multiple sclerosis

PubMed Central

Safari-Alighiarloo, Nahid; Taghizadeh, Mohammad; Tabatabaei, Seyyed Mohammad; Namaki, Saeed

2016-01-01

Background The involvement of multiple genes and missing heritability, which are dominant in complex diseases such as multiple sclerosis (MS), entail using network biology to better elucidate their molecular basis and genetic factors. We therefore aimed to integrate interactome (protein–protein interaction (PPI)) and transcriptomes data to construct and analyze PPI networks for MS disease. Methods Gene expression profiles in paired cerebrospinal fluid (CSF) and peripheral blood mononuclear cells (PBMCs) samples from MS patients, sampled in relapse or remission and controls, were analyzed. Differentially expressed genes which determined only in CSF (MS vs. control) and PBMCs (relapse vs. remission) separately integrated with PPI data to construct the Query-Query PPI (QQPPI) networks. The networks were further analyzed to investigate more central genes, functional modules and complexes involved in MS progression. Results The networks were analyzed and high centrality genes were identified. Exploration of functional modules and complexes showed that the majority of high centrality genes incorporated in biological pathways driving MS pathogenesis. Proteasome and spliceosome were also noticeable in enriched pathways in PBMCs (relapse vs. remission) which were identified by both modularity and clique analyses. Finally, STK4, RB1, CDKN1A, CDK1, RAC1, EZH2, SDCBP genes in CSF (MS vs. control) and CDC37, MAP3K3, MYC genes in PBMCs (relapse vs. remission) were identified as potential candidate genes for MS, which were the more central genes involved in biological pathways. Discussion This study showed that network-based analysis could explicate the complex interplay between biological processes underlying MS. Furthermore, an experimental validation of candidate genes can lead to identification of potential therapeutic targets. PMID:28028462

GraphTeams: a method for discovering spatial gene clusters in Hi-C sequencing data.

PubMed

Schulz, Tizian; Stoye, Jens; Doerr, Daniel

2018-05-08

Hi-C sequencing offers novel, cost-effective means to study the spatial conformation of chromosomes. We use data obtained from Hi-C experiments to provide new evidence for the existence of spatial gene clusters. These are sets of genes with associated functionality that exhibit close proximity to each other in the spatial conformation of chromosomes across several related species. We present the first gene cluster model capable of handling spatial data. Our model generalizes a popular computational model for gene cluster prediction, called δ-teams, from sequences to graphs. Following previous lines of research, we subsequently extend our model to allow for several vertices being associated with the same label. The model, called δ-teams with families, is particular suitable for our application as it enables handling of gene duplicates. We develop algorithmic solutions for both models. We implemented the algorithm for discovering δ-teams with families and integrated it into a fully automated workflow for discovering gene clusters in Hi-C data, called GraphTeams. We applied it to human and mouse data to find intra- and interchromosomal gene cluster candidates. The results include intrachromosomal clusters that seem to exhibit a closer proximity in space than on their chromosomal DNA sequence. We further discovered interchromosomal gene clusters that contain genes from different chromosomes within the human genome, but are located on a single chromosome in mouse. By identifying δ-teams with families, we provide a flexible model to discover gene cluster candidates in Hi-C data. Our analysis of Hi-C data from human and mouse reveals several known gene clusters (thus validating our approach), but also few sparsely studied or possibly unknown gene cluster candidates that could be the source of further experimental investigations.

Genome-wide association study of acute post-surgical pain in humans

PubMed Central

Kim, Hyungsuk; Ramsay, Edward; Lee, Hyewon; Wahl, Sharon; Dionne, Raymond A

2009-01-01

Aims Testing a relatively small genomic region with a few hundred SNPs provides limited information. Genome-wide association studies (GWAS) provide an opportunity to overcome the limitation of candidate gene association studies. Here, we report the results of a GWAS for the responses to an NSAID analgesic. Materials & methods European Americans (60 females and 52 males) undergoing oral surgery were genotyped with Affymetrix 500K SNP assay. Additional SNP genotyping was performed from the gene in linkage disequilibrium with the candidate SNP revealed by the GWAS. Results GWAS revealed a candidate SNP (rs2562456) associated with analgesic onset, which is in linkage disequilibrium with a gene encoding a zinc finger protein. Additional SNP genotyping of ZNF429 confirmed the association with analgesic onset in humans (p = 1.8 × 10−10, degrees of freedom = 103, F = 28.3). We also found candidate loci for the maximum post-operative pain rating (rs17122021, p = 6.9 × 10−7) and post-operative pain onset time (rs6693882, p = 2.1 × 10−6), however, correcting for multiple comparisons did not sustain these genetic associations. Conclusion GWAS for acute clinical pain followed by additional SNP genotyping of a neighboring gene suggests that genetic variations in or near the loci encoding DNA binding proteins play a role in the individual variations in responses to analgesic drugs. PMID:19207018

Linkage Disequilibrium and Haplotype Diversity in the Genes of the Renin–Angiotensin System: Findings From the Family Blood Pressure Program

PubMed Central

Zhu, Xiaofeng; Yan, Denise; Cooper, Richard S.; Luke, Amy; Ikeda, Morna A.; Chang, Yen-Pei C.; Weder, Alan; Chakravarti, Aravinda

2003-01-01

Association studies of candidate genes with complex traits have generally used one or a few single nucleotide polymorphisms (SNPs), although variation in the extent of linkage disequilibrium (LD) within genes markedly influences the sensitivity and precision of association studies. The extent of LD and the underlying haplotype structure for most candidate genes are still unavailable. We sampled 193 blacks (African-Americans) and 160 whites (European-Americans) and estimated the intragenic LD and the haplotype structure in four genes of the renin–angiotensin system. We genotyped 25 SNPs, with all but one of the pairs spaced between 1 and 20 kb, thus providing resolution at small scale. The pattern of LD within a gene was very heterogeneous. Using a robust method to define haplotype blocks, blocks of limited haplotype diversity were identified at each locus; between these blocks, LD was lost owing to the history of recombination events. As anticipated, there was less LD among blacks, the number of haplotypes was substantially larger, and shorter haplotype segments were found, compared with whites. These findings have implications for candidate-gene association studies and indicate that variation between populations of European and African origin in haplotype diversity is characteristic of most genes. [The sequence data described in this paper are available in GenBank under the following accession nos: AGT, MIM 106150; Renin, MIM 179820; ACE, MIM 106180; Angiotensin receptor I, MIM 106165. Supplementary material is available online at http://www.genome.org.] PMID:12566395

Parameter estimation in tree graph metabolic networks.

PubMed

Astola, Laura; Stigter, Hans; Gomez Roldan, Maria Victoria; van Eeuwijk, Fred; Hall, Robert D; Groenenboom, Marian; Molenaar, Jaap J

2016-01-01

We study the glycosylation processes that convert initially toxic substrates to nutritionally valuable metabolites in the flavonoid biosynthesis pathway of tomato (Solanum lycopersicum) seedlings. To estimate the reaction rates we use ordinary differential equations (ODEs) to model the enzyme kinetics. A popular choice is to use a system of linear ODEs with constant kinetic rates or to use Michaelis-Menten kinetics. In reality, the catalytic rates, which are affected among other factors by kinetic constants and enzyme concentrations, are changing in time and with the approaches just mentioned, this phenomenon cannot be described. Another problem is that, in general these kinetic coefficients are not always identifiable. A third problem is that, it is not precisely known which enzymes are catalyzing the observed glycosylation processes. With several hundred potential gene candidates, experimental validation using purified target proteins is expensive and time consuming. We aim at reducing this task via mathematical modeling to allow for the pre-selection of most potential gene candidates. In this article we discuss a fast and relatively simple approach to estimate time varying kinetic rates, with three favorable properties: firstly, it allows for identifiable estimation of time dependent parameters in networks with a tree-like structure. Secondly, it is relatively fast compared to usually applied methods that estimate the model derivatives together with the network parameters. Thirdly, by combining the metabolite concentration data with a corresponding microarray data, it can help in detecting the genes related to the enzymatic processes. By comparing the estimated time dynamics of the catalytic rates with time series gene expression data we may assess potential candidate genes behind enzymatic reactions. As an example, we show how to apply this method to select prominent glycosyltransferase genes in tomato seedlings.

Detection of genomic signatures of recent selection in commercial broiler chickens.

PubMed

Fu, Weixuan; Lee, William R; Abasht, Behnam

2016-08-26

Identification of the genomic signatures of recent selection may help uncover causal polymorphisms controlling traits relevant to recent decades of selective breeding in livestock. In this study, we aimed at detecting signatures of recent selection in commercial broiler chickens using genotype information from single nucleotide polymorphisms (SNPs). A total of 565 chickens from five commercial purebred lines, including three broiler sire (male) lines and two broiler dam (female) lines, were genotyped using the 60K SNP Illumina iSelect chicken array. To detect genomic signatures of recent selection, we applied two methods based on population comparison, cross-population extended haplotype homozygosity (XP-EHH) and cross-population composite likelihood ratio (XP-CLR), and further analyzed the results to find genomic regions under recent selection in multiple purebred lines. A total of 321 candidate selection regions spanning approximately 1.45 % of the chicken genome in each line were detected by consensus of results of both XP-EHH and XP-CLR methods. To minimize false discovery due to genetic drift, only 42 of the candidate selection regions that were shared by 2 or more purebred lines were considered as high-confidence selection regions in the study. Of these 42 regions, 20 were 50 kb or less while 4 regions were larger than 0.5 Mb. In total, 91 genes could be found in the 42 regions, among which 19 regions contained only 1 or 2 genes, and 9 regions were located at gene deserts. Our results provide a genome-wide scan of recent selection signatures in five purebred lines of commercial broiler chickens. We found several candidate genes for recent selection in multiple lines, such as SOX6 (Sex Determining Region Y-Box 6) and cTR (Thyroid hormone receptor beta). These genes may have been under recent selection due to their essential roles in growth, development and reproduction in chickens. Furthermore, our results suggest that in some candidate regions, the same or opposite alleles have been under recent selection in multiple lines. Most of the candidate genes in the selection regions are novel, and as such they should be of great interest for future research into the genetic architecture of traits relevant to modern broiler breeding.

Quality controls in cellular immunotherapies: rapid assessment of clinical grade dendritic cells by gene expression profiling.

PubMed

Castiello, Luciano; Sabatino, Marianna; Zhao, Yingdong; Tumaini, Barbara; Ren, Jiaqiang; Ping, Jin; Wang, Ena; Wood, Lauren V; Marincola, Francesco M; Puri, Raj K; Stroncek, David F

2013-02-01

Cell-based immunotherapies are among the most promising approaches for developing effective and targeted immune response. However, their clinical usefulness and the evaluation of their efficacy rely heavily on complex quality control assessment. Therefore, rapid systematic methods are urgently needed for the in-depth characterization of relevant factors affecting newly developed cell product consistency and the identification of reliable markers for quality control. Using dendritic cells (DCs) as a model, we present a strategy to comprehensively characterize manufactured cellular products in order to define factors affecting their variability, quality and function. After generating clinical grade human monocyte-derived mature DCs (mDCs), we tested by gene expression profiling the degrees of product consistency related to the manufacturing process and variability due to intra- and interdonor factors, and how each factor affects single gene variation. Then, by calculating for each gene an index of variation we selected candidate markers for identity testing, and defined a set of genes that may be useful comparability and potency markers. Subsequently, we confirmed the observed gene index of variation in a larger clinical data set. In conclusion, using high-throughput technology we developed a method for the characterization of cellular therapies and the discovery of novel candidate quality assurance markers.

Next-generation sequencing to identify candidate genes and develop diagnostic markers for a novel Phytophthora resistance gene, RpsHC18, in soybean.

PubMed

Zhong, Chao; Sun, Suli; Li, Yinping; Duan, Canxing; Zhu, Zhendong

2018-03-01

A novel Phytophthora sojae resistance gene RpsHC18 was identified and finely mapped on soybean chromosome 3. Two NBS-LRR candidate genes were identified and two diagnostic markers of RpsHC18 were developed. Phytophthora root rot caused by Phytophthora sojae is a destructive disease of soybean. The most effective disease-control strategy is to deploy resistant cultivars carrying Phytophthora-resistant Rps genes. The soybean cultivar Huachun 18 has a broad and distinct resistance spectrum to 12 P. sojae isolates. Quantitative trait loci sequencing (QTL-seq), based on the whole-genome resequencing (WGRS) of two extreme resistant and susceptible phenotype bulks from an F 2:3 population, was performed, and one 767-kb genomic region with ΔSNP-index ≥ 0.9 on chromosome 3 was identified as the RpsHC18 candidate region in Huachun 18. The candidate region was reduced to a 146-kb region by fine mapping. Nonsynonymous SNP and haplotype analyses were carried out in the 146-kb region among ten soybean genotypes using WGRS. Four specific nonsynonymous SNPs were identified in two nucleotide-binding sites-leucine-rich repeat (NBS-LRR) genes, RpsHC18-NBL1 and RpsHC18-NBL2, which were considered to be the candidate genes. Finally, one specific SNP marker in each candidate gene was successfully developed using a tetra-primer ARMS-PCR assay, and the two markers were verified to be specific for RpsHC18 and to effectively distinguish other known Rps genes. In this study, we applied an integrated genomic-based strategy combining WGRS with traditional genetic mapping to identify RpsHC18 candidate genes and develop diagnostic markers. These results suggest that next-generation sequencing is a precise, rapid and cost-effective way to identify candidate genes and develop diagnostic markers, and it can accelerate Rps gene cloning and marker-assisted selection for breeding of P. sojae-resistant soybean cultivars.

Database of cattle candidate genes and genetic markers for milk production and mastitis

PubMed Central

Ogorevc, J; Kunej, T; Razpet, A; Dovc, P

2009-01-01

A cattle database of candidate genes and genetic markers for milk production and mastitis has been developed to provide an integrated research tool incorporating different types of information supporting a genomic approach to study lactation, udder development and health. The database contains 943 genes and genetic markers involved in mammary gland development and function, representing candidates for further functional studies. The candidate loci were drawn on a genetic map to reveal positional overlaps. For identification of candidate loci, data from seven different research approaches were exploited: (i) gene knockouts or transgenes in mice that result in specific phenotypes associated with mammary gland (143 loci); (ii) cattle QTL for milk production (344) and mastitis related traits (71); (iii) loci with sequence variations that show specific allele-phenotype interactions associated with milk production (24) or mastitis (10) in cattle; (iv) genes with expression profiles associated with milk production (207) or mastitis (107) in cattle or mouse; (v) cattle milk protein genes that exist in different genetic variants (9); (vi) miRNAs expressed in bovine mammary gland (32) and (vii) epigenetically regulated cattle genes associated with mammary gland function (1). Fourty-four genes found by multiple independent analyses were suggested as the most promising candidates and were further in silico analysed for expression levels in lactating mammary gland, genetic variability and top biological functions in functional networks. A miRNA target search for mammary gland expressed miRNAs identified 359 putative binding sites in 3′UTRs of candidate genes. PMID:19508288

HerDing: herb recommendation system to treat diseases using genes and chemicals

PubMed Central

Choi, Wonjun; Choi, Chan-Hun; Kim, Young Ran; Kim, Seon-Jong; Na, Chang-Su; Lee, Hyunju

2016-01-01

In recent years, herbs have been researched for new drug candidates because they have a long empirical history of treating diseases and are relatively free from side effects. Studies to scientifically prove the medical efficacy of herbs for target diseases often spend a considerable amount of time and effort in choosing candidate herbs and in performing experiments to measure changes of marker genes when treating herbs. A computational approach to recommend herbs for treating diseases might be helpful to promote efficiency in the early stage of such studies. Although several databases related to traditional Chinese medicine have been already developed, there is no specialized Web tool yet recommending herbs to treat diseases based on disease-related genes. Therefore, we developed a novel search engine, HerDing, focused on retrieving candidate herb-related information with user search terms (a list of genes, a disease name, a chemical name or an herb name). HerDing was built by integrating public databases and by applying a text-mining method. The HerDing website is free and open to all users, and there is no login requirement. Database URL: http://combio.gist.ac.kr/herding PMID:26980517

HerDing: herb recommendation system to treat diseases using genes and chemicals.

PubMed

Choi, Wonjun; Choi, Chan-Hun; Kim, Young Ran; Kim, Seon-Jong; Na, Chang-Su; Lee, Hyunju

2016-01-01

In recent years, herbs have been researched for new drug candidates because they have a long empirical history of treating diseases and are relatively free from side effects. Studies to scientifically prove the medical efficacy of herbs for target diseases often spend a considerable amount of time and effort in choosing candidate herbs and in performing experiments to measure changes of marker genes when treating herbs. A computational approach to recommend herbs for treating diseases might be helpful to promote efficiency in the early stage of such studies. Although several databases related to traditional Chinese medicine have been already developed, there is no specialized Web tool yet recommending herbs to treat diseases based on disease-related genes. Therefore, we developed a novel search engine, HerDing, focused on retrieving candidate herb-related information with user search terms (a list of genes, a disease name, a chemical name or an herb name). HerDing was built by integrating public databases and by applying a text-mining method. The HerDing website is free and open to all users, and there is no login requirement. Database URL: http://combio.gist.ac.kr/herding. © The Author(s) 2016. Published by Oxford University Press.

Identification and validation of reference genes for qRT-PCR studies of the obligate aphid pathogenic fungus Pandora neoaphidis during different developmental stages.

PubMed

Zhang, Shutao; Chen, Chun; Xie, Tingna; Ye, Sudan

2017-01-01

The selection of stable reference genes is a critical step for the accurate quantification of gene expression. To identify and validate the reference genes in Pandora neoaphidis-an obligate aphid pathogenic fungus-the expression of 13classical candidate reference genes were evaluated by quantitative real-time reverse transcriptase polymerase chain reaction(qPCR) at four developmental stages (conidia, conidia with germ tubes, short hyphae and elongated hyphae). Four statistical algorithms, including geNorm, NormFinder, BestKeeper and Delta Ct method were used to rank putative reference genes according to their expression stability and indicate the best reference gene or combination of reference genes for accurate normalization. The analysis of comprehensive ranking revealed that ACT1and 18Swas the most stably expressed genes throughout the developmental stages. To further validate the suitability of the reference genes identified in this study, the expression of cell division control protein 25 (CDC25) and Chitinase 1(CHI1) genes were used to further confirm the validated candidate reference genes. Our study presented the first systematic study of reference gene(s) selection for P. neoaphidis study and provided guidelines to obtain more accurate qPCR results for future developmental efforts.

Thiopurine pharmacogenomics: association of SNPs with clinical response and functional validation of candidate genes

PubMed Central

Matimba, Alice; Li, Fang; Livshits, Alina; Cartwright, Cher S; Scully, Stephen; Fridley, Brooke L; Jenkins, Gregory; Batzler, Anthony; Wang, Liewei; Weinshilboum, Richard; Lennard, Lynne

2014-01-01

Aim We investigated candidate genes associated with thiopurine metabolism and clinical response in childhood acute lymphoblastic leukemia. Materials & methods We performed genome-wide SNP association studies of 6-thioguanine and 6-mercaptopurine cytotoxicity using lymphoblastoid cell lines. We then genotyped the top SNPs associated with lymphoblastoid cell line cytotoxicity, together with tagSNPs for genes in the ‘thiopurine pathway’ (686 total SNPs), in DNA from 589 Caucasian UK ALL97 patients. Functional validation studies were performed by siRNA knockdown in cancer cell lines. Results SNPs in the thiopurine pathway genes ABCC4, ABCC5, IMPDH1, ITPA, SLC28A3 and XDH, and SNPs located within or near ATP6AP2, FRMD4B, GNG2, KCNMA1 and NME1, were associated with clinical response and measures of thiopurine metabolism. Functional validation showed shifts in cytotoxicity for these genes. Conclusion The clinical response to thiopurines may be regulated by variation in known thiopurine pathway genes and additional novel genes outside of the thiopurine pathway. PMID:24624911

[Genetics of bipolar affective disorders. Current status of research for identification of susceptibility genes].

PubMed

Schumacher, J; Cichon, S; Rietschel, M; Nöthen, M M; Propping, P

2002-07-01

Bipolar affective disorder is a highly heritable condition, as evidenced by twin, family, and adoption studies. However, the mode of inheritance is complex and linkage findings have been difficult to replicate. Despite these limitations, consistent linkage findings have emerged for several chromosomes, notably 3p12-p14, 4p16, 10q25-q26, and 12q23-q24. Three additional areas, 13q32-q33, 18p11-q11, and 22q12-q13, have shown linkage in regions that appear to overlap with linkage findings in schizophrenia. These chromosomal regions might harbour genes that contribute to the development of bipolar affective disorder. Recent candidate gene studies include some positive results for the serotonin transporter gene (5-HTT) on 17q11-q12 and the catechol-O-methyltransferase gene (COMT) on 22q11. New methods are being developed for linkage disequilibrium mapping and candidate gene approaches. One can be optimistic that over the next few years bipolar susceptibility genes will be identified.

Dissecting the organ specificity of insecticide resistance candidate genes in Anopheles gambiae: known and novel candidate genes.

PubMed

Ingham, Victoria A; Jones, Christopher M; Pignatelli, Patricia; Balabanidou, Vasileia; Vontas, John; Wagstaff, Simon C; Moore, Jonathan D; Ranson, Hilary

2014-11-25

The elevated expression of enzymes with insecticide metabolism activity can lead to high levels of insecticide resistance in the malaria vector, Anopheles gambiae. In this study, adult female mosquitoes from an insecticide susceptible and resistant strain were dissected into four different body parts. RNA from each of these samples was used in microarray analysis to determine the enrichment patterns of the key detoxification gene families within the mosquito and to identify additional candidate insecticide resistance genes that may have been overlooked in previous experiments on whole organisms. A general enrichment in the transcription of genes from the four major detoxification gene families (carboxylesterases, glutathione transferases, UDP glucornyltransferases and cytochrome P450s) was observed in the midgut and malpighian tubules. Yet the subset of P450 genes that have previously been implicated in insecticide resistance in An gambiae, show a surprisingly varied profile of tissue enrichment, confirmed by qPCR and, for three candidates, by immunostaining. A stringent selection process was used to define a list of 105 genes that are significantly (p ≤0.001) over expressed in body parts from the resistant versus susceptible strain. Over half of these, including all the cytochrome P450s on this list, were identified in previous whole organism comparisons between the strains, but several new candidates were detected, notably from comparisons of the transcriptomes from dissected abdomen integuments. The use of RNA extracted from the whole organism to identify candidate insecticide resistance genes has a risk of missing candidates if key genes responsible for the phenotype have restricted expression within the body and/or are over expression only in certain tissues. However, as transcription of genes implicated in metabolic resistance to insecticides is not enriched in any one single organ, comparison of the transcriptome of individual dissected body parts cannot be recommended as a preferred means to identify new candidate insecticide resistant genes. Instead the rich data set on in vivo sites of transcription should be consulted when designing follow up qPCR validation steps, or for screening known candidates in field populations.

Horizontal gene transfer in silkworm, Bombyx mori.

PubMed

Zhu, Bo; Lou, Miao-Miao; Xie, Guan-Lin; Zhang, Guo-Qing; Zhou, Xue-Ping; Li, Bin; Jin, Gu-Lei

2011-05-19

The domesticated silkworm, Bombyx mori, is the model insect for the order Lepidoptera, has economically important values, and has gained some representative behavioral characteristics compared to its wild ancestor. The genome of B. mori has been fully sequenced while function analysis of BmChi-h and BmSuc1 genes revealed that horizontal gene transfer (HGT) maybe bestow a clear selective advantage to B. mori. However, the role of HGT in the evolutionary history of B. mori is largely unexplored. In this study, we compare the whole genome of B. mori with those of 382 prokaryotic and eukaryotic species to investigate the potential HGTs. Ten candidate HGT events were defined in B. mori by comprehensive sequence analysis using Maximum Likelihood and Bayesian method combining with EST checking. Phylogenetic analysis of the candidate HGT genes suggested that one HGT was plant-to- B. mori transfer while nine were bacteria-to- B. mori transfer. Furthermore, functional analysis based on expression, coexpression and related literature searching revealed that several HGT candidate genes have added important characters, such as resistance to pathogen, to B. mori. Results from this study clearly demonstrated that HGTs play an important role in the evolution of B. mori although the number of HGT events in B. mori is in general smaller than those of microbes and other insects. In particular, interdomain HGTs in B. mori may give rise to functional, persistent, and possibly evolutionarily significant new genes.

Neuroprotective therapies in glaucoma: II. Genetic nanotechnology tools.

PubMed

Nafissi, Nafiseh; Foldvari, Marianna

2015-01-01

Neurotrophic factor genome engineering could have many potential applications not only in the deeper understanding of neurodegenerative disorders but also in improved therapeutics. The fields of nanomedicine, regenerative medicine, and gene/cell-based therapy have been revolutionized by the development of safer and efficient non-viral technologies for gene delivery and genome editing with modern techniques for insertion of the neurotrophic factors into clinically relevant cells for a more sustained pharmaceutical effect. It has been suggested that the long-term expression of neurotrophic factors is the ultimate approach to prevent and/or treat neurodegenerative disorders such as glaucoma in patients who do not respond to available treatments or are at the progressive stage of the disease. Recent preclinical research suggests that novel neuroprotective gene and cell therapeutics could be promising approaches for both non-invasive neuroprotection and regenerative functions in the eye. Several progenitor and retinal cell types have been investigated as potential candidates for glaucoma neurotrophin therapy either as targets for gene therapy, options for cell replacement therapy, or as vehicles for gene delivery. Therefore, in parallel with deeper understanding of the specific protective effects of different neurotrophic factors and the potential therapeutic cell candidates for glaucoma neuroprotection, the development of non-invasive and highly specific gene delivery methods with safe and effective technologies to modify cell candidates for life-long neuroprotection in the eye is essential before investing in this field.

Noncoding copy-number variations are associated with congenital limb malformation.

PubMed

Flöttmann, Ricarda; Kragesteen, Bjørt K; Geuer, Sinje; Socha, Magdalena; Allou, Lila; Sowińska-Seidler, Anna; Bosquillon de Jarcy, Laure; Wagner, Johannes; Jamsheer, Aleksander; Oehl-Jaschkowitz, Barbara; Wittler, Lars; de Silva, Deepthi; Kurth, Ingo; Maya, Idit; Santos-Simarro, Fernando; Hülsemann, Wiebke; Klopocki, Eva; Mountford, Roger; Fryer, Alan; Borck, Guntram; Horn, Denise; Lapunzina, Pablo; Wilson, Meredith; Mascrez, Bénédicte; Duboule, Denis; Mundlos, Stefan; Spielmann, Malte

2017-10-12

PurposeCopy-number variants (CNVs) are generally interpreted by linking the effects of gene dosage with phenotypes. The clinical interpretation of noncoding CNVs remains challenging. We investigated the percentage of disease-associated CNVs in patients with congenital limb malformations that affect noncoding cis-regulatory sequences versus genes sensitive to gene dosage effects.MethodsWe applied high-resolution copy-number analysis to 340 unrelated individuals with isolated limb malformation. To investigate novel candidate CNVs, we re-engineered human CNVs in mice using clustered regularly interspaced short palindromic repeats (CRISPR)-based genome editing.ResultsOf the individuals studied, 10% harbored CNVs segregating with the phenotype in the affected families. We identified 31 CNVs previously associated with congenital limb malformations and four novel candidate CNVs. Most of the disease-associated CNVs (57%) affected the noncoding cis-regulatory genome, while only 43% included a known disease gene and were likely to result from gene dosage effects. In transgenic mice harboring four novel candidate CNVs, we observed altered gene expression in all cases, indicating that the CNVs had a regulatory effect either by changing the enhancer dosage or altering the topological associating domain architecture of the genome.ConclusionOur findings suggest that CNVs affecting noncoding regulatory elements are a major cause of congenital limb malformations.Genetics in Medicine advance online publication, 12 October 2017; doi:10.1038/gim.2017.154.

Meta-review of protein network regulating obesity between validated obesity candidate genes in the white adipose tissue of high-fat diet-induced obese C57BL/6J mice.

PubMed

Kim, Eunjung; Kim, Eun Jung; Seo, Seung-Won; Hur, Cheol-Goo; McGregor, Robin A; Choi, Myung-Sook

2014-01-01

Worldwide obesity and related comorbidities are increasing, but identifying new therapeutic targets remains a challenge. A plethora of microarray studies in diet-induced obesity models has provided large datasets of obesity associated genes. In this review, we describe an approach to examine the underlying molecular network regulating obesity, and we discuss interactions between obesity candidate genes. We conducted network analysis on functional protein-protein interactions associated with 25 obesity candidate genes identified in a literature-driven approach based on published microarray studies of diet-induced obesity. The obesity candidate genes were closely associated with lipid metabolism and inflammation. Peroxisome proliferator activated receptor gamma (Pparg) appeared to be a core obesity gene, and obesity candidate genes were highly interconnected, suggesting a coordinately regulated molecular network in adipose tissue. In conclusion, the current network analysis approach may help elucidate the underlying molecular network regulating obesity and identify anti-obesity targets for therapeutic intervention.

Whole exome sequencing identifies novel candidate genes that modify chronic obstructive pulmonary disease susceptibility.

PubMed

Bruse, Shannon; Moreau, Michael; Bromberg, Yana; Jang, Jun-Ho; Wang, Nan; Ha, Hongseok; Picchi, Maria; Lin, Yong; Langley, Raymond J; Qualls, Clifford; Klensney-Tait, Julia; Zabner, Joseph; Leng, Shuguang; Mao, Jenny; Belinsky, Steven A; Xing, Jinchuan; Nyunoya, Toru

2016-01-07

Chronic obstructive pulmonary disease (COPD) is characterized by an irreversible airflow limitation in response to inhalation of noxious stimuli, such as cigarette smoke. However, only 15-20 % smokers manifest COPD, suggesting a role for genetic predisposition. Although genome-wide association studies have identified common genetic variants that are associated with susceptibility to COPD, effect sizes of the identified variants are modest, as is the total heritability accounted for by these variants. In this study, an extreme phenotype exome sequencing study was combined with in vitro modeling to identify COPD candidate genes. We performed whole exome sequencing of 62 highly susceptible smokers and 30 exceptionally resistant smokers to identify rare variants that may contribute to disease risk or resistance to COPD. This was a cross-sectional case-control study without therapeutic intervention or longitudinal follow-up information. We identified candidate genes based on rare variant analyses and evaluated exonic variants to pinpoint individual genes whose function was computationally established to be significantly different between susceptible and resistant smokers. Top scoring candidate genes from these analyses were further filtered by requiring that each gene be expressed in human bronchial epithelial cells (HBECs). A total of 81 candidate genes were thus selected for in vitro functional testing in cigarette smoke extract (CSE)-exposed HBECs. Using small interfering RNA (siRNA)-mediated gene silencing experiments, we showed that silencing of several candidate genes augmented CSE-induced cytotoxicity in vitro. Our integrative analysis through both genetic and functional approaches identified two candidate genes (TACC2 and MYO1E) that augment cigarette smoke (CS)-induced cytotoxicity and, potentially, COPD susceptibility.

The genome sequence of the most widely cultivated cacao type and its use to identify candidate genes regulating pod color

USDA-ARS?s Scientific Manuscript database

Background: Theobroma cacao L. cultivar Matina 1-6 belongs to the most cultivated cacao type. The availability of its genome sequence and methods for identifying genes responsible for important cacao traits will aid cacao researchers and breeders. Results: We describe the sequencing and assembly of...

Cognitive Functioning in Affected Sibling Pairs with ADHD: Familial Clustering and Dopamine Genes

ERIC Educational Resources Information Center

Loo, Sandra K.; Rich, Erika Carpenter; Ishii, Janeen; McGough, James; McCracken, James; Nelson, Stanley; Smalley, Susan L.

2008-01-01

Background: This paper examines familiality and candidate gene associations of cognitive measures as potential endophenotypes in attention-deficit/hyperactivity disorder (ADHD). Methods: The sample consists of 540 participants, aged 6 to 18, who were diagnosed with ADHD from 251 families recruited for a larger genetic study of ADHD. All members of…

Differences in Brain Transcriptomes of Closely Related Baikal Coregonid Species

PubMed Central

Bychenko, Oksana S.; Sukhanova, Lyubov V.; Azhikina, Tatyana L.; Skvortsov, Timofey A.; Belomestnykh, Tuyana V.; Sverdlov, Eugene D.

2014-01-01

The aim of this work was to get deeper insight into genetic factors involved in the adaptive divergence of closely related species, specifically two representatives of Baikal coregonids—Baikal whitefish (Coregonus baicalensis Dybowski) and Baikal omul (Coregonus migratorius Georgi)—that diverged from a common ancestor as recently as 10–20 thousand years ago. Using the Serial Analysis of Gene Expression method, we obtained libraries of short representative cDNA sequences (tags) from the brains of Baikal whitefish and omul. A comparative analysis of the libraries revealed quantitative differences among ~4% tags of the fishes under study. Based on the similarity of these tags with cDNA of known organisms, we identified candidate genes taking part in adaptive divergence. The most important candidate genes related to the adaptation of Baikal whitefish and Baikal omul, identified in this work, belong to the genes of cell metabolism, nervous and immune systems, protein synthesis, and regulatory genes as well as to DTSsa4 Tc1-like transposons which are widespread among fishes. PMID:24719892

Identification of Reference Genes for Normalizing Quantitative Real-Time PCR in Urechis unicinctus

NASA Astrophysics Data System (ADS)

Bai, Yajiao; Zhou, Di; Wei, Maokai; Xie, Yueyang; Gao, Beibei; Qin, Zhenkui; Zhang, Zhifeng

2018-06-01

The reverse transcription quantitative real-time PCR (RT-qPCR) has become one of the most important techniques of studying gene expression. A set of valid reference genes are essential for the accurate normalization of data. In this study, five candidate genes were analyzed with geNorm, NormFinder, BestKeeper and ΔCt methods to identify the genes stably expressed in echiuran Urechis unicinctus, an important commercial marine benthic worm, under abiotic (sulfide stress) and normal (adult tissues, embryos and larvae at different development stages) conditions. The comprehensive results indicated that the expression of TBP was the most stable at sulfide stress and in developmental process, while the expression of EF- 1- α was the most stable at sulfide stress and in various tissues. TBP and EF- 1- α were recommended as a suitable reference gene combination to accurately normalize the expression of target genes at sulfide stress; and EF- 1- α, TBP and TUB were considered as a potential reference gene combination for normalizing the expression of target genes in different tissues. No suitable gene combination was obtained among these five candidate genes for normalizing the expression of target genes for developmental process of U. unicinctus. Our results provided a valuable support for quantifying gene expression using RT-qPCR in U. unicinctus.

Investigating Gene Function in Cereal Rust Fungi by Plant-Mediated Virus-Induced Gene Silencing.

PubMed

Panwar, Vinay; Bakkeren, Guus

2017-01-01

Cereal rust fungi are destructive pathogens, threatening grain production worldwide. Targeted breeding for resistance utilizing host resistance genes has been effective. However, breakdown of resistance occurs frequently and continued efforts are needed to understand how these fungi overcome resistance and to expand the range of available resistance genes. Whole genome sequencing, transcriptomic and proteomic studies followed by genome-wide computational and comparative analyses have identified large repertoire of genes in rust fungi among which are candidates predicted to code for pathogenicity and virulence factors. Some of these genes represent defence triggering avirulence effectors. However, functions of most genes still needs to be assessed to understand the biology of these obligate biotrophic pathogens. Since genetic manipulations such as gene deletion and genetic transformation are not yet feasible in rust fungi, performing functional gene studies is challenging. Recently, Host-induced gene silencing (HIGS) has emerged as a useful tool to characterize gene function in rust fungi while infecting and growing in host plants. We utilized Barley stripe mosaic virus-mediated virus induced gene silencing (BSMV-VIGS) to induce HIGS of candidate rust fungal genes in the wheat host to determine their role in plant-fungal interactions. Here, we describe the methods for using BSMV-VIGS in wheat for functional genomics study in cereal rust fungi.

Genome-wide association study of CSF biomarkers Abeta1-42, t-tau, and p-tau181p in the ADNI cohort.

PubMed

Kim, S; Swaminathan, S; Shen, L; Risacher, S L; Nho, K; Foroud, T; Shaw, L M; Trojanowski, J Q; Potkin, S G; Huentelman, M J; Craig, D W; DeChairo, B M; Aisen, P S; Petersen, R C; Weiner, M W; Saykin, A J

2011-01-04

CSF levels of Aβ1-42, t-tau, and p-tau181p are potential early diagnostic markers for probable Alzheimer disease (AD). The influence of genetic variation on these markers has been investigated for candidate genes but not on a genome-wide basis. We report a genome-wide association study (GWAS) of CSF biomarkers (Aβ1-42, t-tau, p-tau181p, p-tau181p/Aβ1-42, and t-tau/Aβ1-42). A total of 374 non-Hispanic Caucasian participants in the Alzheimer's Disease Neuroimaging Initiative cohort with quality-controlled CSF and genotype data were included in this analysis. The main effect of single nucleotide polymorphisms (SNPs) under an additive genetic model was assessed on each of 5 CSF biomarkers. The p values of all SNPs for each CSF biomarker were adjusted for multiple comparisons by the Bonferroni method. We focused on SNPs with corrected p<0.01 (uncorrected p<3.10×10(-8)) and secondarily examined SNPs with uncorrected p values less than 10(-5) to identify potential candidates. Four SNPs in the regions of the APOE, LOC100129500, TOMM40, and EPC2 genes reached genome-wide significance for associations with one or more CSF biomarkers. SNPs in CCDC134, ABCG2, SREBF2, and NFATC4, although not reaching genome-wide significance, were identified as potential candidates. In addition to known candidate genes, APOE, TOMM40, and one hypothetical gene LOC100129500 partially overlapping APOE; one novel gene, EPC2, and several other interesting genes were associated with CSF biomarkers that are related to AD. These findings, especially the new EPC2 results, require replication in independent cohorts.

Survival dimensionality reduction (SDR): development and clinical application of an innovative approach to detect epistasis in presence of right-censored data.

PubMed

Beretta, Lorenzo; Santaniello, Alessandro; van Riel, Piet L C M; Coenen, Marieke J H; Scorza, Raffaella

2010-08-06

Epistasis is recognized as a fundamental part of the genetic architecture of individuals. Several computational approaches have been developed to model gene-gene interactions in case-control studies, however, none of them is suitable for time-dependent analysis. Herein we introduce the Survival Dimensionality Reduction (SDR) algorithm, a non-parametric method specifically designed to detect epistasis in lifetime datasets. The algorithm requires neither specification about the underlying survival distribution nor about the underlying interaction model and proved satisfactorily powerful to detect a set of causative genes in synthetic epistatic lifetime datasets with a limited number of samples and high degree of right-censorship (up to 70%). The SDR method was then applied to a series of 386 Dutch patients with active rheumatoid arthritis that were treated with anti-TNF biological agents. Among a set of 39 candidate genes, none of which showed a detectable marginal effect on anti-TNF responses, the SDR algorithm did find that the rs1801274 SNP in the Fc gamma RIIa gene and the rs10954213 SNP in the IRF5 gene non-linearly interact to predict clinical remission after anti-TNF biologicals. Simulation studies and application in a real-world setting support the capability of the SDR algorithm to model epistatic interactions in candidate-genes studies in presence of right-censored data. http://sourceforge.net/projects/sdrproject/.

Pediatric Glioblastoma Therapies Based on Patient-Derived Stem Cell Resources

DTIC Science & Technology

2014-11-01

genomic DNA and then subjected to Illumina high-throughput sequencing . In this analysis, shRNAs lost in the GSC population represent candidate gene...and genomic DNA and then subjected to Illumina high-throughput sequencing . In this analysis, shRNAs lost in the GSC population represent candidate...PRISM 7900 Sequence Detection System ( Genomics Resource, FHCRC). Relative transcript abundance was analyzed using the 2−ΔΔCt method. TRIzol (Invitrogen

Evaluating Reported Candidate Gene Associations with Polycystic Ovary Syndrome

PubMed Central

Pau, Cindy; Saxena, Richa; Welt, Corrine Kolka

2013-01-01

Objective To replicate variants in candidate genes associated with PCOS in a population of European PCOS and control subjects. Design Case-control association analysis and meta-analysis. Setting Major academic hospital Patients Women of European ancestry with PCOS (n=525) and controls (n=472), aged 18 to 45 years. Intervention Variants previously associated with PCOS in candidate gene studies were genotyped (n=39). Metabolic, reproductive and anthropomorphic parameters were examined as a function of the candidate variants. All genetic association analyses were adjusted for age, BMI and ancestry and were reported after correction for multiple testing. Main Outcome Measure Association of candidate gene variants with PCOS. Results Three variants, rs3797179 (SRD5A1), rs12473543 (POMC), and rs1501299 (ADIPOQ), were nominally associated with PCOS. However, they did not remain significant after correction for multiple testing and none of the variants replicated in a sufficiently powered meta-analysis. Variants in the FBN3 gene (rs17202517 and rs73503752) were associated with smaller waist circumferences and variant rs727428 in the SHBG gene was associated with lower SHBG levels. Conclusion Previously identified variants in candidate genes do not appear to be associated with PCOS risk. PMID:23375202

QTL analysis of dietary obesity in C57BL/6byj X 129P3/J F2 mice: diet- and sex-dependent effects.

PubMed

Lin, Cailu; Theodorides, Maria L; McDaniel, Amanda H; Tordoff, Michael G; Zhang, Qinmin; Li, Xia; Bosak, Natalia; Bachmanov, Alexander A; Reed, Danielle R

2013-01-01

Obesity is a heritable trait caused by complex interactions between genes and environment, including diet. Gene-by-diet interactions are difficult to study in humans because the human diet is hard to control. Here, we used mice to study dietary obesity genes, by four methods. First, we bred 213 F2 mice from strains that are susceptible [C57BL/6ByJ (B6)] or resistant [129P3/J (129)] to dietary obesity. Percent body fat was assessed after mice ate low-energy diet and again after the same mice ate high-energy diet for 8 weeks. Linkage analyses identified QTLs associated with dietary obesity. Three methods were used to filter candidate genes within the QTL regions: (a) association mapping was conducted using >40 strains; (b) differential gene expression and (c) comparison of genomic DNA sequence, using two strains closely related to the progenitor strains from Experiment 1. The QTL effects depended on whether the mice were male or female or which diet they were recently fed. After feeding a low-energy diet, percent body fat was linked to chr 7 (LOD=3.42). After feeding a high-energy diet, percent body fat was linked to chr 9 (Obq5; LOD=3.88), chr 12 (Obq34; LOD=3.88), and chr 17 (LOD=4.56). The Chr 7 and 12 QTLs were sex dependent and all QTL were diet-dependent. The combination of filtering methods highlighted seven candidate genes within the QTL locus boundaries: Crx, Dmpk, Ahr, Mrpl28, Glo1, Tubb5, and Mut. However, these filtering methods have limitations so gene identification will require alternative strategies, such as the construction of congenics with very small donor regions.

Mining new crystal protein genes from Bacillus thuringiensis on the basis of mixed plasmid-enriched genome sequencing and a computational pipeline.

PubMed

Ye, Weixing; Zhu, Lei; Liu, Yingying; Crickmore, Neil; Peng, Donghai; Ruan, Lifang; Sun, Ming

2012-07-01

We have designed a high-throughput system for the identification of novel crystal protein genes (cry) from Bacillus thuringiensis strains. The system was developed with two goals: (i) to acquire the mixed plasmid-enriched genomic sequence of B. thuringiensis using next-generation sequencing biotechnology, and (ii) to identify cry genes with a computational pipeline (using BtToxin_scanner). In our pipeline method, we employed three different kinds of well-developed prediction methods, BLAST, hidden Markov model (HMM), and support vector machine (SVM), to predict the presence of Cry toxin genes. The pipeline proved to be fast (average speed, 1.02 Mb/min for proteins and open reading frames [ORFs] and 1.80 Mb/min for nucleotide sequences), sensitive (it detected 40% more protein toxin genes than a keyword extraction method using genomic sequences downloaded from GenBank), and highly specific. Twenty-one strains from our laboratory's collection were selected based on their plasmid pattern and/or crystal morphology. The plasmid-enriched genomic DNA was extracted from these strains and mixed for Illumina sequencing. The sequencing data were de novo assembled, and a total of 113 candidate cry sequences were identified using the computational pipeline. Twenty-seven candidate sequences were selected on the basis of their low level of sequence identity to known cry genes, and eight full-length genes were obtained with PCR. Finally, three new cry-type genes (primary ranks) and five cry holotypes, which were designated cry8Ac1, cry7Ha1, cry21Ca1, cry32Fa1, and cry21Da1 by the B. thuringiensis Toxin Nomenclature Committee, were identified. The system described here is both efficient and cost-effective and can greatly accelerate the discovery of novel cry genes.

[Stability analysis of reference gene based on real-time PCR in Artemisia annua under cadmium treatment].

PubMed

Zhou, Liang-Yun; Mo, Ge; Wang, Sheng; Tang, Jin-Fu; Yue, Hong; Huang, Lu-Qi; Shao, Ai-Juan; Guo, Lan-Ping

2014-03-01

In this study, Actin, 18S rRNA, PAL, GAPDH and CPR of Artemisia annua were selected as candidate reference genes, and their gene-specific primers for real-time PCR were designed, then geNorm, NormFinder, BestKeeper, Delta CT and RefFinder were used to evaluate their expression stability in the leaves of A. annua under treatment of different concentrations of Cd, with the purpose of finding a reliable reference gene to ensure the reliability of gene-expression analysis. The results showed that there were some significant differences among the candidate reference genes under different treatments and the order of expression stability of candidate reference gene was Actin > 18S rRNA > PAL > GAPDH > CPR. These results suggested that Actin, 18S rRNA and PAL could be used as ideal reference genes of gene expression analysis in A. annua and multiple internal control genes were adopted for results calibration. In addition, differences in expression stability of candidate reference genes in the leaves of A. annua under the same concentrations of Cd were observed, which suggested that the screening of candidate reference genes was needed even under the same treatment. To our best knowledge, this study for the first time provided the ideal reference genes under Cd treatment in the leaves of A. annua and offered reference for the gene expression analysis of A. annua under other conditions.

Interactogeneous: Disease Gene Prioritization Using Heterogeneous Networks and Full Topology Scores

PubMed Central

Gonçalves, Joana P.; Francisco, Alexandre P.; Moreau, Yves; Madeira, Sara C.

2012-01-01

Disease gene prioritization aims to suggest potential implications of genes in disease susceptibility. Often accomplished in a guilt-by-association scheme, promising candidates are sorted according to their relatedness to known disease genes. Network-based methods have been successfully exploiting this concept by capturing the interaction of genes or proteins into a score. Nonetheless, most current approaches yield at least some of the following limitations: (1) networks comprise only curated physical interactions leading to poor genome coverage and density, and bias toward a particular source; (2) scores focus on adjacencies (direct links) or the most direct paths (shortest paths) within a constrained neighborhood around the disease genes, ignoring potentially informative indirect paths; (3) global clustering is widely applied to partition the network in an unsupervised manner, attributing little importance to prior knowledge; (4) confidence weights and their contribution to edge differentiation and ranking reliability are often disregarded. We hypothesize that network-based prioritization related to local clustering on graphs and considering full topology of weighted gene association networks integrating heterogeneous sources should overcome the above challenges. We term such a strategy Interactogeneous. We conducted cross-validation tests to assess the impact of network sources, alternative path inclusion and confidence weights on the prioritization of putative genes for 29 diseases. Heat diffusion ranking proved the best prioritization method overall, increasing the gap to neighborhood and shortest paths scores mostly on single source networks. Heterogeneous associations consistently delivered superior performance over single source data across the majority of methods. Results on the contribution of confidence weights were inconclusive. Finally, the best Interactogeneous strategy, heat diffusion ranking and associations from the STRING database, was used to prioritize genes for Parkinson’s disease. This method effectively recovered known genes and uncovered interesting candidates which could be linked to pathogenic mechanisms of the disease. PMID:23185389

Prediction and Validation of Disease Genes Using HeteSim Scores.

PubMed

Zeng, Xiangxiang; Liao, Yuanlu; Liu, Yuansheng; Zou, Quan

2017-01-01

Deciphering the gene disease association is an important goal in biomedical research. In this paper, we use a novel relevance measure, called HeteSim, to prioritize candidate disease genes. Two methods based on heterogeneous networks constructed using protein-protein interaction, gene-phenotype associations, and phenotype-phenotype similarity, are presented. In HeteSim_MultiPath (HSMP), HeteSim scores of different paths are combined with a constant that dampens the contributions of longer paths. In HeteSim_SVM (HSSVM), HeteSim scores are combined with a machine learning method. The 3-fold experiments show that our non-machine learning method HSMP performs better than the existing non-machine learning methods, our machine learning method HSSVM obtains similar accuracy with the best existing machine learning method CATAPULT. From the analysis of the top 10 predicted genes for different diseases, we found that HSSVM avoid the disadvantage of the existing machine learning based methods, which always predict similar genes for different diseases. The data sets and Matlab code for the two methods are freely available for download at http://lab.malab.cn/data/HeteSim/index.jsp.

Prediction of Human Disease Genes by Human-Mouse Conserved Coexpression Analysis

PubMed Central

Grassi, Elena; Damasco, Christian; Silengo, Lorenzo; Oti, Martin; Provero, Paolo; Di Cunto, Ferdinando

2008-01-01

Background Even in the post-genomic era, the identification of candidate genes within loci associated with human genetic diseases is a very demanding task, because the critical region may typically contain hundreds of positional candidates. Since genes implicated in similar phenotypes tend to share very similar expression profiles, high throughput gene expression data may represent a very important resource to identify the best candidates for sequencing. However, so far, gene coexpression has not been used very successfully to prioritize positional candidates. Methodology/Principal Findings We show that it is possible to reliably identify disease-relevant relationships among genes from massive microarray datasets by concentrating only on genes sharing similar expression profiles in both human and mouse. Moreover, we show systematically that the integration of human-mouse conserved coexpression with a phenotype similarity map allows the efficient identification of disease genes in large genomic regions. Finally, using this approach on 850 OMIM loci characterized by an unknown molecular basis, we propose high-probability candidates for 81 genetic diseases. Conclusion Our results demonstrate that conserved coexpression, even at the human-mouse phylogenetic distance, represents a very strong criterion to predict disease-relevant relationships among human genes. PMID:18369433

Genome-wide association study identified genetic variations and candidate genes for plant architecture component traits in Chinese upland cotton.

PubMed

Su, Junji; Li, Libei; Zhang, Chi; Wang, Caixiang; Gu, Lijiao; Wang, Hantao; Wei, Hengling; Liu, Qibao; Huang, Long; Yu, Shuxun

2018-06-01

Thirty significant associations between 22 SNPs and five plant architecture component traits in Chinese upland cotton were identified via GWAS. Four peak SNP loci located on chromosome D03 were simultaneously associated with more plant architecture component traits. A candidate gene, Gh_D03G0922, might be responsible for plant height in upland cotton. A compact plant architecture is increasingly required for mechanized harvesting processes in China. Therefore, cotton plant architecture is an important trait, and its components, such as plant height, fruit branch length and fruit branch angle, affect the suitability of a cultivar for mechanized harvesting. To determine the genetic basis of cotton plant architecture, a genome-wide association study (GWAS) was performed using a panel composed of 355 accessions and 93,250 single nucleotide polymorphisms (SNPs) identified using the specific-locus amplified fragment sequencing method. Thirty significant associations between 22 SNPs and five plant architecture component traits were identified via GWAS. Most importantly, four peak SNP loci located on chromosome D03 were simultaneously associated with more plant architecture component traits, and these SNPs were harbored in one linkage disequilibrium block. Furthermore, 21 candidate genes for plant architecture were predicted in a 0.95-Mb region including the four peak SNPs. One of these genes (Gh_D03G0922) was near the significant SNP D03_31584163 (8.40 kb), and its Arabidopsis homologs contain MADS-box domains that might be involved in plant growth and development. qRT-PCR showed that the expression of Gh_D03G0922 was upregulated in the apical buds and young leaves of the short and compact cotton varieties, and virus-induced gene silencing (VIGS) proved that the silenced plants exhibited increased PH. These results indicate that Gh_D03G0922 is likely the candidate gene for PH in cotton. The genetic variations and candidate genes identified in this study lay a foundation for cultivating moderately short and compact varieties in future Chinese cotton-breeding programs.

Lumbosacral stenosis in Labrador retriever military working dogs - an exomic exploratory study.

PubMed

Mukherjee, Meenakshi; Jones, Jeryl C; Yao, Jianbo

2017-01-01

Canine lumbosacral stenosis is defined as narrowing of the caudal lumbar and/or sacral vertebral canal. A risk factor for neurologic problems in many large sized breeds, lumbosacral stenosis can also cause early retirement in Labrador retriever military working dogs. Though vital for conservative management of the condition, early detection is complicated by the ambiguous nature of clinical signs of lumbosacral stenosis in stoic and high-drive Labrador retriever military working dogs. Though clinical diagnoses of lumbosacral stenosis using CT imaging are standard, they are usually not performed unless dogs present with clinical symptoms. Understanding the underlying genomic mechanisms would be beneficial in developing early detection methods for lumbosacral stenosis, which could prevent premature retirement in working dogs. The exomes of 8 young Labrador retriever military working dogs (4 affected and 4 unaffected by lumbosacral stenosis, phenotypically selected by CT image analyses from 40 dogs with no reported clinical signs of the condition) were sequenced to identify and annotate exonic variants between dogs negative and positive for lumbosacral stenosis. Two-hundred and fifty-two variants were detected to be homozygous for the wild allele and either homozygous or heterozygous for the variant allele. Seventeen non-disruptive variants were detected that could affect protein effectiveness in 7 annotated (SCN1B, RGS9BP, ASXL3, TTR, LRRC16B, PTPRO, ZBBX) and 3 predicted genes (EEF1A1, DNAJA1, ZFX). No exonic variants were detected in any of the canine orthologues for human lumbar spinal stenosis candidate genes. TTR (transthyretin) gene could be a possible candidate for lumbosacral stenosis in Labrador retrievers based on previous human studies that have reported an association between human lumbar spinal stenosis and transthyretin protein amyloidosis. Other genes identified with exonic variants in this study but with no known published association with lumbosacral stenosis and/or lumbar spinal stenosis could also be candidate genes for future canine lumbosacral stenosis studies but their roles remain currently unknown. Human lumbar spinal stenosis candidate genes also cannot be ruled out as lumbosacral stenosis candidate genes. More definitive genetic investigations of this condition are needed before any genetic test for lumbosacral stenosis in Labrador retriever can be developed.

Identification of Inherited Retinal Disease-Associated Genetic Variants in 11 Candidate Genes.

PubMed

Astuti, Galuh D N; van den Born, L Ingeborgh; Khan, M Imran; Hamel, Christian P; Bocquet, Béatrice; Manes, Gaël; Quinodoz, Mathieu; Ali, Manir; Toomes, Carmel; McKibbin, Martin; El-Asrag, Mohammed E; Haer-Wigman, Lonneke; Inglehearn, Chris F; Black, Graeme C M; Hoyng, Carel B; Cremers, Frans P M; Roosing, Susanne

2018-01-10

Inherited retinal diseases (IRDs) display an enormous genetic heterogeneity. Whole exome sequencing (WES) recently identified genes that were mutated in a small proportion of IRD cases. Consequently, finding a second case or family carrying pathogenic variants in the same candidate gene often is challenging. In this study, we searched for novel candidate IRD gene-associated variants in isolated IRD families, assessed their causality, and searched for novel genotype-phenotype correlations. Whole exome sequencing was performed in 11 probands affected with IRDs. Homozygosity mapping data was available for five cases. Variants with minor allele frequencies ≤ 0.5% in public databases were selected as candidate disease-causing variants. These variants were ranked based on their: (a) presence in a gene that was previously implicated in IRD; (b) minor allele frequency in the Exome Aggregation Consortium database (ExAC); (c) in silico pathogenicity assessment using the combined annotation dependent depletion (CADD) score; and (d) interaction of the corresponding protein with known IRD-associated proteins. Twelve unique variants were found in 11 different genes in 11 IRD probands. Novel autosomal recessive and dominant inheritance patterns were found for variants in Small Nuclear Ribonucleoprotein U5 Subunit 200 ( SNRNP200 ) and Zinc Finger Protein 513 ( ZNF513 ), respectively. Using our pathogenicity assessment, a variant in DEAH-Box Helicase 32 ( DHX32 ) was the top ranked novel candidate gene to be associated with IRDs, followed by eight medium and lower ranked candidate genes. The identification of candidate disease-associated sequence variants in 11 single families underscores the notion that the previously identified IRD-associated genes collectively carry > 90% of the defects implicated in IRDs. To identify multiple patients or families with variants in the same gene and thereby provide extra proof for pathogenicity, worldwide data sharing is needed.

Gene-gene interactions among genetic variants from obesity candidate genes for nonobese and obese populations in type 2 diabetes.

PubMed

Lin, Eugene; Pei, Dee; Huang, Yi-Jen; Hsieh, Chang-Hsun; Wu, Lawrence Shih-Hsin

2009-08-01

Recent studies indicate that obesity may play a key role in modulating genetic predispositions to type 2 diabetes (T2D). This study examines the main effects of both single-locus and multilocus interactions among genetic variants in Taiwanese obese and nonobese individuals to test the hypothesis that obesity-related genes may contribute to the etiology of T2D independently and/or through such complex interactions. We genotyped 11 single nucleotide polymorphisms for 10 obesity candidate genes including adrenergic beta-2-receptor surface, adrenergic beta-3-receptor surface, angiotensinogen, fat mass and obesity associated gene, guanine nucleotide binding protein beta polypeptide 3 (GNB3), interleukin 6 receptor, proprotein convertase subtilisin/kexin type 1 (PCSK1), uncoupling protein 1, uncoupling protein 2, and uncoupling protein 3. There were 389 patients diagnosed with T2D and 186 age- and sex-matched controls. Single-locus analyses showed significant main effects of the GNB3 and PCSK1 genes on the risk of T2D among the nonobese group (p = 0.002 and 0.047, respectively). Further, interactions involving GNB3 and PCSK1 were suggested among the nonobese population using the generalized multifactor dimensionality reduction method (p = 0.001). In addition, interactions among angiotensinogen, fat mass and obesity associated gene, GNB3, and uncoupling protein 3 genes were found in a significant four-locus generalized multifactor dimensionality reduction model among the obese population (p = 0.001). The results suggest that the single nucleotide polymorphisms from the obesity candidate genes may contribute to the risk of T2D independently and/or in an interactive manner according to the presence or absence of obesity.

Scanning the genome for gene single nucleotide polymorphisms involved in adaptive population differentiation in white spruce

PubMed Central

Namroud, Marie-Claire; Beaulieu, Jean; Juge, Nicolas; Laroche, Jérôme; Bousquet, Jean

2008-01-01

Conifers are characterized by a large genome size and a rapid decay of linkage disequilibrium, most often within gene limits. Genome scans based on noncoding markers are less likely to detect molecular adaptation linked to genes in these species. In this study, we assessed the effectiveness of a genome-wide single nucleotide polymorphism (SNP) scan focused on expressed genes in detecting local adaptation in a conifer species. Samples were collected from six natural populations of white spruce (Picea glauca) moderately differentiated for several quantitative characters. A total of 534 SNPs representing 345 expressed genes were analysed. Genes potentially under natural selection were identified by estimating the differentiation in SNP frequencies among populations (FST) and identifying outliers, and by estimating local differentiation using a Bayesian approach. Both average expected heterozygosity and population differentiation estimates (HE = 0.270 and FST = 0.006) were comparable to those obtained with other genetic markers. Of all genes, 5.5% were identified as outliers with FST at the 95% confidence level, while 14% were identified as candidates for local adaptation with the Bayesian method. There was some overlap between the two gene sets. More than half of the candidate genes for local adaptation were specific to the warmest population, about 20% to the most arid population, and 15% to the coldest and most humid higher altitude population. These adaptive trends were consistent with the genes’ putative functions and the divergence in quantitative traits noted among the populations. The results suggest that an approach separating the locus and population effects is useful to identify genes potentially under selection. These candidates are worth exploring in more details at the physiological and ecological levels. PMID:18662225

Bioinformatics analysis and detection of gelatinase encoded gene in Lysinibacillussphaericus

NASA Astrophysics Data System (ADS)

Repin, Rul Aisyah Mat; Mutalib, Sahilah Abdul; Shahimi, Safiyyah; Khalid, Rozida Mohd.; Ayob, Mohd. Khan; Bakar, Mohd. Faizal Abu; Isa, Mohd Noor Mat

2016-11-01

In this study, we performed bioinformatics analysis toward genome sequence of Lysinibacillussphaericus (L. sphaericus) to determine gene encoded for gelatinase. L. sphaericus was isolated from soil and gelatinase species-specific bacterium to porcine and bovine gelatin. This bacterium offers the possibility of enzymes production which is specific to both species of meat, respectively. The main focus of this research is to identify the gelatinase encoded gene within the bacteria of L. Sphaericus using bioinformatics analysis of partially sequence genome. From the research study, three candidate gene were identified which was, gelatinase candidate gene 1 (P1), NODE_71_length_93919_cov_158.931839_21 which containing 1563 base pair (bp) in size with 520 amino acids sequence; Secondly, gelatinase candidate gene 2 (P2), NODE_23_length_52851_cov_190.061386_17 which containing 1776 bp in size with 591 amino acids sequence; and Thirdly, gelatinase candidate gene 3 (P3), NODE_106_length_32943_cov_169.147919_8 containing 1701 bp in size with 566 amino acids sequence. Three pairs of oligonucleotide primers were designed and namely as, F1, R1, F2, R2, F3 and R3 were targeted short sequences of cDNA by PCR. The amplicons were reliably results in 1563 bp in size for candidate gene P1 and 1701 bp in size for candidate gene P3. Therefore, the results of bioinformatics analysis of L. Sphaericus resulting in gene encoded gelatinase were identified.

Systematic identification and validation of candidate genes for detection of circulating tumor cells in peripheral blood specimens of colorectal cancer patients.

PubMed

Findeisen, Peter; Röckel, Matthias; Nees, Matthias; Röder, Christian; Kienle, Peter; Von Knebel Doeberitz, Magnus; Kalthoff, Holger; Neumaier, Michael

2008-11-01

The presence of tumor cells in peripheral blood is being regarded increasingly as a clinically relevant prognostic factor for colorectal cancer patients. Current molecular methods are very sensitive but due to low specificity their diagnostic value is limited. This study was undertaken in order to systematically identify and validate new colorectal cancer (CRC) marker genes for improved detection of minimal residual disease in peripheral blood mononuclear cells of colorectal cancer patients. Marker genes with upregulated gene expression in colorectal cancer tissue and cell lines were identified using microarray experiments and publicly available gene expression data. A systematic iterative approach was used to reduce a set of 346 candidate genes, reportedly associated with CRC to a selection of candidate genes that were then further validated by relative quantitative real-time RT-PCR. Analytical sensitivity of RT-PCR assays was determined by spiking experiments with CRC cells. Diagnostic sensitivity as well as specificity was tested on a control group consisting of 18 CRC patients compared to 12 individuals without malignant disease. From a total of 346-screened genes only serine (or cysteine) proteinase inhibitor, clade B (ovalbumin), member 5 (SERPINB5) showed significantly elevated transcript levels in peripheral venous blood specimens of tumor patients when compared to the nonmalignant control group. These results were confirmed by analysis of an enlarged collective consisting of 63 CRC patients and 36 control individuals without malignant disease. In conclusion SERPINB5 seems to be a promising marker for detection of circulating tumor cells in peripheral blood of colorectal cancer patients.

Genome-Wide Association Mapping Combined with Reverse Genetics Identifies New Effectors of Low Water Potential-Induced Proline Accumulation in Arabidopsis1[W][OPEN

PubMed Central

Verslues, Paul E.; Lasky, Jesse R.; Juenger, Thomas E.; Liu, Tzu-Wen; Kumar, M. Nagaraj

2014-01-01

Arabidopsis (Arabidopsis thaliana) exhibits natural genetic variation in drought response, including varying levels of proline (Pro) accumulation under low water potential. As Pro accumulation is potentially important for stress tolerance and cellular redox control, we conducted a genome-wide association (GWAS) study of low water potential-induced Pro accumulation using a panel of natural accessions and publicly available single-nucleotide polymorphism (SNP) data sets. Candidate genomic regions were prioritized for subsequent study using metrics considering both the strength and spatial clustering of the association signal. These analyses found many candidate regions likely containing gene(s) influencing Pro accumulation. Reverse genetic analysis of several candidates identified new Pro effector genes, including thioredoxins and several genes encoding Universal Stress Protein A domain proteins. These new Pro effector genes further link Pro accumulation to cellular redox and energy status. Additional new Pro effector genes found include the mitochondrial protease LON1, ribosomal protein RPL24A, protein phosphatase 2A subunit A3, a MADS box protein, and a nucleoside triphosphate hydrolase. Several of these new Pro effector genes were from regions with multiple SNPs, each having moderate association with Pro accumulation. This pattern supports the use of summary approaches that incorporate clusters of SNP associations in addition to consideration of individual SNP probability values. Further GWAS-guided reverse genetics promises to find additional effectors of Pro accumulation. The combination of GWAS and reverse genetics to efficiently identify new effector genes may be especially applicable for traits difficult to analyze by other genetic screening methods. PMID:24218491

The Arabidopsis translatome cell-specific mRNA atlas: Mining suberin and cutin lipid monomer biosynthesis genes as an example for data application.

PubMed

Mustroph, Angelika; Bailey-Serres, Julia

2010-03-01

Plants consist of distinct cell types distinguished by position, morphological features and metabolic activities. We recently developed a method to extract cell-type specific mRNA populations by immunopurification of ribosome-associated mRNAs. Microarray profiles of 21 cell-specific mRNA populations from seedling roots and shoots comprise the Arabidopsis Translatome dataset. This gene expression atlas provides a new tool for the study of cell-specific processes. Here we provide an example of how genes involved in a pathway limited to one or few cell-types can be further characterized and new candidate genes can be predicted. Cells of the root endodermis produce suberin as an inner barrier between the cortex and stele, whereas the shoot epidermal cells form cutin as a barrier to the external environment. Both polymers consist of fatty acid derivates, and share biosynthetic origins. We use the Arabidopsis Translatome dataset to demonstrate the significant cell-specific expression patterns of genes involved in those biosynthetic processes and suggest new candidate genes in the biosynthesis of suberin and cutin.

Association and linkage studies of candidate genes involved in GABAergic neurotransmission in lithium-responsive bipolar disorder.

PubMed Central

Duffy, A; Turecki, G; Grof, P; Cavazzoni, P; Grof, E; Joober, R; Ahrens, B; Berghöfer, A; Müller-Oerlinghausen, B; Dvoráková, M; Libigerová, E; Vojtĕchovský, M; Zvolský, P; Nilsson, A; Licht, R W; Rasmussen, N A; Schou, M; Vestergaard, P; Holzinger, A; Schumann, C; Thau, K; Robertson, C; Rouleau, G A; Alda, M

2000-01-01

OBJECTIVE: To test for genetic linkage and association with GABAergic candidate genes in lithium-responsive bipolar disorder. DESIGN: Polymorphisms located in genes that code for GABRA3, GABRA5 and GABRB3 subunits of the GABAA receptor were investigated using association and linkage strategies. PARTICIPANTS: A total of 138 patients with bipolar 1 disorder with a clear response to lithium prophylaxis, selected from specialized lithium clinics in Canada and Europe that are part of the International Group for the Study of Lithium-Treated Patients, and 108 psychiatrically healthy controls. Families of 24 probands were suitable for linkage analysis. OUTCOME MEASURES: The association between the candidate genes and patients with bipolar disorder versus that of controls and genetic linkage within families. RESULTS: There was no significant association or linkage found between lithium-responsive bipolar disorder and the GABAergic candidate genes investigated. CONCLUSIONS: This study does not support a major role for the GABAergic candidate genes tested in lithium-responsive bipolar disorder. PMID:11022400

Identifying Cancer Driver Genes Using Replication-Incompetent Retroviral Vectors

PubMed Central

Bii, Victor M.; Trobridge, Grant D.

2016-01-01

Identifying novel genes that drive tumor metastasis and drug resistance has significant potential to improve patient outcomes. High-throughput sequencing approaches have identified cancer genes, but distinguishing driver genes from passengers remains challenging. Insertional mutagenesis screens using replication-incompetent retroviral vectors have emerged as a powerful tool to identify cancer genes. Unlike replicating retroviruses and transposons, replication-incompetent retroviral vectors lack additional mutagenesis events that can complicate the identification of driver mutations from passenger mutations. They can also be used for almost any human cancer due to the broad tropism of the vectors. Replication-incompetent retroviral vectors have the ability to dysregulate nearby cancer genes via several mechanisms including enhancer-mediated activation of gene promoters. The integrated provirus acts as a unique molecular tag for nearby candidate driver genes which can be rapidly identified using well established methods that utilize next generation sequencing and bioinformatics programs. Recently, retroviral vector screens have been used to efficiently identify candidate driver genes in prostate, breast, liver and pancreatic cancers. Validated driver genes can be potential therapeutic targets and biomarkers. In this review, we describe the emergence of retroviral insertional mutagenesis screens using replication-incompetent retroviral vectors as a novel tool to identify cancer driver genes in different cancer types. PMID:27792127

What Do Beginner Biology Teacher Candidates Know of Genetics and Genes?

ERIC Educational Resources Information Center

Oztas, Fulya; Oztas, Haydar

2016-01-01

Misconceptions are a barrier to understanding biology hence, to promote meaningful learning, it is necessary to overcome these difficulties with the help of different instructional methods rather than traditional instructional methods. Therefore it could be very interesting to find out "how students' prior knowledge of genetics affects…

A Model-Based Approach for Identifying Signatures of Ancient Balancing Selection in Genetic Data

PubMed Central

DeGiorgio, Michael; Lohmueller, Kirk E.; Nielsen, Rasmus

2014-01-01

While much effort has focused on detecting positive and negative directional selection in the human genome, relatively little work has been devoted to balancing selection. This lack of attention is likely due to the paucity of sophisticated methods for identifying sites under balancing selection. Here we develop two composite likelihood ratio tests for detecting balancing selection. Using simulations, we show that these methods outperform competing methods under a variety of assumptions and demographic models. We apply the new methods to whole-genome human data, and find a number of previously-identified loci with strong evidence of balancing selection, including several HLA genes. Additionally, we find evidence for many novel candidates, the strongest of which is FANK1, an imprinted gene that suppresses apoptosis, is expressed during meiosis in males, and displays marginal signs of segregation distortion. We hypothesize that balancing selection acts on this locus to stabilize the segregation distortion and negative fitness effects of the distorter allele. Thus, our methods are able to reproduce many previously-hypothesized signals of balancing selection, as well as discover novel interesting candidates. PMID:25144706

A model-based approach for identifying signatures of ancient balancing selection in genetic data.

PubMed

DeGiorgio, Michael; Lohmueller, Kirk E; Nielsen, Rasmus

2014-08-01

While much effort has focused on detecting positive and negative directional selection in the human genome, relatively little work has been devoted to balancing selection. This lack of attention is likely due to the paucity of sophisticated methods for identifying sites under balancing selection. Here we develop two composite likelihood ratio tests for detecting balancing selection. Using simulations, we show that these methods outperform competing methods under a variety of assumptions and demographic models. We apply the new methods to whole-genome human data, and find a number of previously-identified loci with strong evidence of balancing selection, including several HLA genes. Additionally, we find evidence for many novel candidates, the strongest of which is FANK1, an imprinted gene that suppresses apoptosis, is expressed during meiosis in males, and displays marginal signs of segregation distortion. We hypothesize that balancing selection acts on this locus to stabilize the segregation distortion and negative fitness effects of the distorter allele. Thus, our methods are able to reproduce many previously-hypothesized signals of balancing selection, as well as discover novel interesting candidates.

Identification of candidate genes associated with porcine meat color traits by genome-wide transcriptome analysis.

PubMed

Li, Bojiang; Dong, Chao; Li, Pinghua; Ren, Zhuqing; Wang, Han; Yu, Fengxiang; Ning, Caibo; Liu, Kaiqing; Wei, Wei; Huang, Ruihua; Chen, Jie; Wu, Wangjun; Liu, Honglin

2016-10-17

Meat color is considered to be the most important indicator of meat quality, however, the molecular mechanisms underlying traits related to meat color remain mostly unknown. In this study, to elucidate the molecular basis of meat color, we constructed six cDNA libraries from biceps femoris (Bf) and soleus (Sol), which exhibit obvious differences in meat color, and analyzed the whole-transcriptome differences between Bf (white muscle) and Sol (red muscle) using high-throughput sequencing technology. Using DEseq2 method, we identified 138 differentially expressed genes (DEGs) between Bf and Sol. Using DEGseq method, we identified 770, 810, and 476 DEGs in comparisons between Bf and Sol in three separate animals. Of these DEGs, 52 were overlapping DEGs. Using these data, we determined the enriched GO terms, metabolic pathways and candidate genes associated with meat color traits. Additionally, we mapped 114 non-redundant DEGs to the meat color QTLs via a comparative analysis with the porcine quantitative trait loci (QTL) database. Overall, our data serve as a valuable resource for identifying genes whose functions are critical for meat color traits and can accelerate studies of the molecular mechanisms of meat color formation.

Identification of candidate genes associated with porcine meat color traits by genome-wide transcriptome analysis

PubMed Central

Li, Bojiang; Dong, Chao; Li, Pinghua; Ren, Zhuqing; Wang, Han; Yu, Fengxiang; Ning, Caibo; Liu, Kaiqing; Wei, Wei; Huang, Ruihua; Chen, Jie; Wu, Wangjun; Liu, Honglin

2016-01-01

Meat color is considered to be the most important indicator of meat quality, however, the molecular mechanisms underlying traits related to meat color remain mostly unknown. In this study, to elucidate the molecular basis of meat color, we constructed six cDNA libraries from biceps femoris (Bf) and soleus (Sol), which exhibit obvious differences in meat color, and analyzed the whole-transcriptome differences between Bf (white muscle) and Sol (red muscle) using high-throughput sequencing technology. Using DEseq2 method, we identified 138 differentially expressed genes (DEGs) between Bf and Sol. Using DEGseq method, we identified 770, 810, and 476 DEGs in comparisons between Bf and Sol in three separate animals. Of these DEGs, 52 were overlapping DEGs. Using these data, we determined the enriched GO terms, metabolic pathways and candidate genes associated with meat color traits. Additionally, we mapped 114 non-redundant DEGs to the meat color QTLs via a comparative analysis with the porcine quantitative trait loci (QTL) database. Overall, our data serve as a valuable resource for identifying genes whose functions are critical for meat color traits and can accelerate studies of the molecular mechanisms of meat color formation. PMID:27748458

A random set scoring model for prioritization of disease candidate genes using protein complexes and data-mining of GeneRIF, OMIM and PubMed records.

PubMed

Jiang, Li; Edwards, Stefan M; Thomsen, Bo; Workman, Christopher T; Guldbrandtsen, Bernt; Sørensen, Peter

2014-09-24

Prioritizing genetic variants is a challenge because disease susceptibility loci are often located in genes of unknown function or the relationship with the corresponding phenotype is unclear. A global data-mining exercise on the biomedical literature can establish the phenotypic profile of genes with respect to their connection to disease phenotypes. The importance of protein-protein interaction networks in the genetic heterogeneity of common diseases or complex traits is becoming increasingly recognized. Thus, the development of a network-based approach combined with phenotypic profiling would be useful for disease gene prioritization. We developed a random-set scoring model and implemented it to quantify phenotype relevance in a network-based disease gene-prioritization approach. We validated our approach based on different gene phenotypic profiles, which were generated from PubMed abstracts, OMIM, and GeneRIF records. We also investigated the validity of several vocabulary filters and different likelihood thresholds for predicted protein-protein interactions in terms of their effect on the network-based gene-prioritization approach, which relies on text-mining of the phenotype data. Our method demonstrated good precision and sensitivity compared with those of two alternative complex-based prioritization approaches. We then conducted a global ranking of all human genes according to their relevance to a range of human diseases. The resulting accurate ranking of known causal genes supported the reliability of our approach. Moreover, these data suggest many promising novel candidate genes for human disorders that have a complex mode of inheritance. We have implemented and validated a network-based approach to prioritize genes for human diseases based on their phenotypic profile. We have devised a powerful and transparent tool to identify and rank candidate genes. Our global gene prioritization provides a unique resource for the biological interpretation of data from genome-wide association studies, and will help in the understanding of how the associated genetic variants influence disease or quantitative phenotypes.

Defining the proximal border of the Huntington disease candidate region by multipoint recombination analyses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Skraastad, M.I.; De Rooij, K.E.; De Koning Gans, P.A.M.

1993-06-01

The candidate region for the Huntington disease (HD) gene has been narrowed down to a 2.2-Mb region between D4S10 and D4S98 on the short arm of chromosome 4. To map the HD gene within this candidate region 65 Dutch HD families were studied. In total 338 informative meioses were analyzed and 11 multiple informative crossovers were detected. Assuming a minimum number of recombinations and no double recombinations, the multiple informative crossovers are consistent with one specific genetic order for 12 loci: D4S10-(D4S81,D4S126)-D4S125-(D4S127,D4S95)-D4S43-(D4S115, D4S96, D4S111, D4S90, D4S141).This is in agreement with the known data derived from similar and other methods. Themore » loci between brackets could not be mapped relative to each other. In the family material, two informative three-point marker recombination events were detected in the proximal HD candidate region, which are also informative for HD. Both recombination events map the HD gene distal to D4S81 and most likely distal to D4S125, narrowing down the HD candidate region to a 1.7-Mb region between D4S125 and D4S98. 39 refs., 3 figs., 2 tabs.« less

The database of chromosome imbalance regions and genes resided in lung cancer from Asian and Caucasian identified by array-comparative genomic hybridization

PubMed Central

2012-01-01

Background Cancer-related genes show racial differences. Therefore, identification and characterization of DNA copy number alteration regions in different racial groups helps to dissect the mechanism of tumorigenesis. Methods Array-comparative genomic hybridization (array-CGH) was analyzed for DNA copy number profile in 40 Asian and 20 Caucasian lung cancer patients. Three methods including MetaCore analysis for disease and pathway correlations, concordance analysis between array-CGH database and the expression array database, and literature search for copy number variation genes were performed to select novel lung cancer candidate genes. Four candidate oncogenes were validated for DNA copy number and mRNA and protein expression by quantitative polymerase chain reaction (qPCR), chromogenic in situ hybridization (CISH), reverse transcriptase-qPCR (RT-qPCR), and immunohistochemistry (IHC) in more patients. Results We identified 20 chromosomal imbalance regions harboring 459 genes for Caucasian and 17 regions containing 476 genes for Asian lung cancer patients. Seven common chromosomal imbalance regions harboring 117 genes, included gain on 3p13-14, 6p22.1, 9q21.13, 13q14.1, and 17p13.3; and loss on 3p22.2-22.3 and 13q13.3 were found both in Asian and Caucasian patients. Gene validation for four genes including ARHGAP19 (10q24.1) functioning in Rho activity control, FRAT2 (10q24.1) involved in Wnt signaling, PAFAH1B1 (17p13.3) functioning in motility control, and ZNF322A (6p22.1) involved in MAPK signaling was performed using qPCR and RT-qPCR. Mean gene dosage and mRNA expression level of the four candidate genes in tumor tissues were significantly higher than the corresponding normal tissues (P<0.001~P=0.06). In addition, CISH analysis of patients indicated that copy number amplification indeed occurred for ARHGAP19 and ZNF322A genes in lung cancer patients. IHC analysis of paraffin blocks from Asian Caucasian patients demonstrated that the frequency of PAFAH1B1 protein overexpression was 68% in Asian and 70% in Caucasian. Conclusions Our study provides an invaluable database revealing common and differential imbalance regions at specific chromosomes among Asian and Caucasian lung cancer patients. Four validation methods confirmed our database, which would help in further studies on the mechanism of lung tumorigenesis. PMID:22691236

Defining a new candidate gene for amelogenesis imperfecta: from molecular genetics to biochemistry.

PubMed

Urzúa, Blanca; Ortega-Pinto, Ana; Morales-Bozo, Irene; Rojas-Alcayaga, Gonzalo; Cifuentes, Víctor

2011-02-01

Amelogenesis imperfecta is a group of genetic conditions that affect the structure and clinical appearance of tooth enamel. The types (hypoplastic, hypocalcified, and hypomature) are correlated with defects in different stages of the process of enamel synthesis. Autosomal dominant, recessive, and X-linked types have been previously described. These disorders are considered clinically and genetically heterogeneous in etiology, involving a variety of genes, such as AMELX, ENAM, DLX3, FAM83H, MMP-20, KLK4, and WDR72. The mutations identified within these causal genes explain less than half of all cases of amelogenesis imperfecta. Most of the candidate and causal genes currently identified encode proteins involved in enamel synthesis. We think it is necessary to refocus the search for candidate genes using biochemical processes. This review provides theoretical evidence that the human SLC4A4 gene (sodium bicarbonate cotransporter) may be a new candidate gene.

A public platform for the verification of the phenotypic effect of candidate genes for resistance to aflatoxin accumulation and Aspergillus flavus infection in maize.

PubMed

Warburton, Marilyn L; Williams, William Paul; Hawkins, Leigh; Bridges, Susan; Gresham, Cathy; Harper, Jonathan; Ozkan, Seval; Mylroie, J Erik; Shan, Xueyan

2011-07-01

A public candidate gene testing pipeline for resistance to aflatoxin accumulation or Aspergillus flavus infection in maize is presented here. The pipeline consists of steps for identifying, testing, and verifying the association of selected maize gene sequences with resistance under field conditions. Resources include a database of genetic and protein sequences associated with the reduction in aflatoxin contamination from previous studies; eight diverse inbred maize lines for polymorphism identification within any maize gene sequence; four Quantitative Trait Loci (QTL) mapping populations and one association mapping panel, all phenotyped for aflatoxin accumulation resistance and associated phenotypes; and capacity for Insertion/Deletion (InDel) and SNP genotyping in the population(s) for mapping. To date, ten genes have been identified as possible candidate genes and put through the candidate gene testing pipeline, and results are presented here to demonstrate the utility of the pipeline.

ENU Mutagenesis in Mice Identifies Candidate Genes For Hypogonadism

PubMed Central

Weiss, Jeffrey; Hurley, Lisa A.; Harris, Rebecca M.; Finlayson, Courtney; Tong, Minghan; Fisher, Lisa A.; Moran, Jennifer L.; Beier, David R.; Mason, Christopher; Jameson, J. Larry

2012-01-01

Genome-wide mutagenesis was performed in mice to identify candidate genes for male infertility, for which the predominant causes remain idiopathic. Mice were mutagenized using N-ethyl-N-nitrosourea (ENU), bred, and screened for phenotypes associated with the male urogenital system. Fifteen heritable lines were isolated and chromosomal loci were assigned using low density genome-wide SNP arrays. Ten of the fifteen lines were pursued further using higher resolution SNP analysis to narrow the candidate gene regions. Exon sequencing of candidate genes identified mutations in mice with cystic kidneys (Bicc1), cryptorchidism (Rxfp2), restricted germ cell deficiency (Plk4), and severe germ cell deficiency (Prdm9). In two other lines with severe hypogonadism candidate sequencing failed to identify mutations, suggesting defects in genes with previously undocumented roles in gonadal function. These genomic intervals were sequenced in their entirety and a candidate mutation was identified in SnrpE in one of the two lines. The line harboring the SnrpE variant retains substantial spermatogenesis despite small testis size, an unusual phenotype. In addition to the reproductive defects, heritable phenotypes were observed in mice with ataxia (Myo5a), tremors (Pmp22), growth retardation (unknown gene), and hydrocephalus (unknown gene). These results demonstrate that the ENU screen is an effective tool for identifying potential causes of male infertility. PMID:22258617

Identifying the candidate genes involved in the calyx abscission process of 'Kuerlexiangli' (Pyrus sinkiangensis Yu) by digital transcript abundance measurements.

PubMed

Qi, Xiaoxiao; Wu, Jun; Wang, Lifen; Li, Leiting; Cao, Yufen; Tian, Luming; Dong, Xingguang; Zhang, Shaoling

2013-10-23

'Kuerlexiangli' (Pyrus sinkiangensis Yu), a native pear of Xinjiang, China, is an important agricultural fruit and primary export to the international market. However, fruit with persistent calyxes affect fruit shape and quality. Although several studies have looked into the physiological aspects of the calyx abscission process, the underlying molecular mechanisms remain unknown. In order to better understand the molecular basis of the process of calyx abscission, materials at three critical stages of regulation, with 6000 × Flusilazole plus 300 × PBO treatment (calyx abscising treatment) and 50 mg.L-1GA3 treatment (calyx persisting treatment), were collected and cDNA fragments were sequenced using digital transcript abundance measurements to identify candidate genes. Digital transcript abundance measurements was performed using high-throughput Illumina GAII sequencing on seven samples that were collected at three important stages of the calyx abscission process with chemical agent treatments promoting calyx abscission and persistence. Altogether more than 251,123,845 high quality reads were obtained with approximately 8.0 M raw data for each library. The values of 69.85%-71.90% of clean data in the digital transcript abundance measurements could be mapped to the pear genome database. There were 12,054 differentially expressed genes having Gene Ontology (GO) terms and associating with 251 Kyoto Encyclopedia of Genes and Genomes (KEGG) defined pathways. The differentially expressed genes correlated with calyx abscission were mainly involved in photosynthesis, plant hormone signal transduction, cell wall modification, transcriptional regulation, and carbohydrate metabolism. Furthermore, candidate calyx abscission-specific genes, e.g. Inflorescence deficient in abscission gene, were identified. Quantitative real-time PCR was used to confirm the digital transcript abundance measurements results. We identified candidate genes that showed highly dynamic changes in expression during the calyx abscission process. These genes are potential targets for future functional characterization and should be valuable for exploration of the mechanisms of calyx abscission, and eventually for developing methods based on small molecule application to induce calyx abscission in fruit production.

Multilocus patterns of nucleotide diversity and divergence reveal positive selection at candidate genes related to cold hardiness in coastal Douglas Fir (Pseudotsuga menziesii var. menziesii).

PubMed

Eckert, Andrew J; Wegrzyn, Jill L; Pande, Barnaly; Jermstad, Kathleen D; Lee, Jennifer M; Liechty, John D; Tearse, Brandon R; Krutovsky, Konstantin V; Neale, David B

2009-09-01

Forest trees exhibit remarkable adaptations to their environments. The genetic basis for phenotypic adaptation to climatic gradients has been established through a long history of common garden, provenance, and genecological studies. The identities of genes underlying these traits, however, have remained elusive and thus so have the patterns of adaptive molecular diversity in forest tree genomes. Here, we report an analysis of diversity and divergence for a set of 121 cold-hardiness candidate genes in coastal Douglas fir (Pseudotsuga menziesii var. menziesii). Application of several different tests for neutrality, including those that incorporated demographic models, revealed signatures of selection consistent with selective sweeps at three to eight loci, depending upon the severity of a bottleneck event and the method used to detect selection. Given the high levels of recombination, these candidate genes are likely to be closely linked to the target of selection if not the genes themselves. Putative homologs in Arabidopsis act primarily to stabilize the plasma membrane and protect against denaturation of proteins at freezing temperatures. These results indicate that surveys of nucleotide diversity and divergence, when framed within the context of further association mapping experiments, will come full circle with respect to their utility in the dissection of complex phenotypic traits into their genetic components.

Genome-wide Discovery of Circular RNAs in the Leaf and Seedling Tissues of Arabidopsis Thaliana

PubMed Central

Dou, Yongchao; Li, Shengjun; Yang, Weilong; Liu, Kan; Du, Qian; Ren, Guodong; Yu, Bin; Zhang, Chi

2017-01-01

Background: Recently, identification and functional studies of circular RNAs, a type of non-coding RNAs arising from a ligation of 3’ and 5’ ends of a linear RNA molecule, were conducted in mammalian cells with the development of RNA-seq technology. Method: Since compared with animals, studies on circular RNAs in plants are less thorough, a genome-wide identification of circular RNA candidates in Arabidopsis was conducted with our own developed bioinformatics tool to several existing RNA-seq datasets specifically for non-coding RNAs. Results: A total of 164 circular RNA candidates were identified from RNA-seq data, and 4 circular RNA transcripts, including both exonic and intronic circular RNAs, were experimentally validated. Interestingly, our results show that circular RNA transcripts are enriched in the photosynthesis system for the leaf tissue and correlated to the higher expression levels of their parent genes. Sixteen out of all 40 genes that have circular RNA candidates are related to the photosynthesis system, and out of the total 146 exonic circular RNA candidates, 63 are found in chloroplast. PMID:29081691

The cld mutation: narrowing the critical chromosomal region and selecting candidate genes.

PubMed

Péterfy, Miklós; Mao, Hui Z; Doolittle, Mark H

2006-10-01

Combined lipase deficiency (cld) is a recessive, lethal mutation specific to the tw73 haplotype on mouse Chromosome 17. While the cld mutation results in lipase proteins that are inactive, aggregated, and retained in the endoplasmic reticulum (ER), it maps separately from the lipase structural genes. We have narrowed the gene critical region by about 50% using the tw18 haplotype for deletion mapping and a recombinant chromosome used originally to map cld with respect to the phenotypic marker tf. The region now extends from 22 to 25.6 Mbp on the wild-type chromosome, currently containing 149 genes and 50 expressed sequence tags (ESTs). To identify the affected gene, we have selected candidates based on their known role in associated biological processes, cellular components, and molecular functions that best fit with the predicted function of the cld gene. A secondary approach was based on differences in mRNA levels between mutant (cld/cld) and unaffected (+/cld) cells. Using both approaches, we have identified seven functional candidates with an ER localization and/or an involvement in protein maturation and folding that could explain the lipase deficiency, and six expression candidates that exhibit large differences in mRNA levels between mutant and unaffected cells. Significantly, two genes were found to be candidates with regard to both function and expression, thus emerging as the strongest candidates for cld. We discuss the implications of our mapping results and our selection of candidates with respect to other genes, deletions, and mutations occurring in the cld critical region.

Modulators of the microRNA biogenesis pathway via arrayed lentiviral enabled RNAi screening for drug and biomarker discovery

PubMed Central

Shum, David; Bhinder, Bhavneet; Djaballah, Hakim

2013-01-01

MicroRNAs (miRNAs) are small endogenous and conserved non-coding RNA molecules that regulate gene expression. Although the first miRNA was discovered well over sixteen years ago, little is known about their biogenesis and it is only recently that we have begun to understand their scope and diversity. For this purpose, we performed an RNAi screen aimed at identifying genes involved in their biogenesis pathway with a potential use as biomarkers. Using a previously developed miRNA 21 (miR-21) EGFP-based biosensor cell based assay monitoring green fluorescence enhancements, we performed an arrayed short hairpin RNA (shRNA) screen against a lentiviral particle ready TRC1 library covering 16,039 genes in 384-well plate format, and interrogating the genome one gene at a time building a panoramic view of endogenous miRNA activity. Using the BDA method for RNAi data analysis, we nominate 497 gene candidates the knockdown of which increased the EGFP fluorescence and yielding an initial hit rate of 3.09%; of which only 22, with reported validated clones, are deemed high-confidence gene candidates. An unexpected and surprising result was that only DROSHA was identified as a hit out of the seven core essential miRNA biogenesis genes; suggesting that perhaps intracellular shRNA processing into the correct duplex may be cell dependent and with differential outcome. Biological classification revealed several major control junctions among them genes involved in transport and vesicular trafficking. In summary, we report on 22 high confidence gene candidate regulators of miRNA biogenesis with potential use in drug and biomarker discovery. PMID:23977983

Selection of Valid Reference Genes for Reverse Transcription Quantitative PCR Analysis in Heliconius numata (Lepidoptera: Nymphalidae)

PubMed Central

Chouteau, Mathieu; Whibley, Annabel; Joron, Mathieu; Llaurens, Violaine

2016-01-01

Identifying the genetic basis of adaptive variation is challenging in non-model organisms and quantitative real time PCR. is a useful tool for validating predictions regarding the expression of candidate genes. However, comparing expression levels in different conditions requires rigorous experimental design and statistical analyses. Here, we focused on the neotropical passion-vine butterflies Heliconius, non-model species studied in evolutionary biology for their adaptive variation in wing color patterns involved in mimicry and in the signaling of their toxicity to predators. We aimed at selecting stable reference genes to be used for normalization of gene expression data in RT-qPCR analyses from developing wing discs according to the minimal guidelines described in Minimum Information for publication of Quantitative Real-Time PCR Experiments (MIQE). To design internal RT-qPCR controls, we studied the stability of expression of nine candidate reference genes (actin, annexin, eF1α, FK506BP, PolyABP, PolyUBQ, RpL3, RPS3A, and tubulin) at two developmental stages (prepupal and pupal) using three widely used programs (GeNorm, NormFinder and BestKeeper). Results showed that, despite differences in statistical methods, genes RpL3, eF1α, polyABP, and annexin were stably expressed in wing discs in late larval and pupal stages of Heliconius numata. This combination of genes may be used as a reference for a reliable study of differential expression in wings for instance for genes involved in important phenotypic variation, such as wing color pattern variation. Through this example, we provide general useful technical recommendations as well as relevant statistical strategies for evolutionary biologists aiming to identify candidate-genes involved adaptive variation in non-model organisms. PMID:27271971

Biological pathways, candidate genes and molecular markers associated with quality-of-life domains: an update

PubMed Central

Sprangers, Mirjam A.G.; Thong, Melissa S.Y.; Bartels, Meike; Barsevick, Andrea; Ordoñana, Juan; Shi, Qiuling; Wang, Xin Shelley; Klepstad, Pål; Wierenga, Eddy A.; Singh, Jasvinder A.; Sloan, Jeff A.

2014-01-01

Background There is compelling evidence of a genetic foundation of patient-reported QOL. Given the rapid development of substantial scientific advances in this area of research, the current paper updates and extends reviews published in 2010. Objectives The objective is to provide an updated overview of the biological pathways, candidate genes and molecular markers involved in fatigue, pain, negative (depressed mood) and positive (well-being/happiness) emotional functioning, social functioning, and overall QOL. Methods We followed a purposeful search algorithm of existing literature to capture empirical papers investigating the relationship between biological pathways and molecular markers and the identified QOL domains. Results Multiple major pathways are involved in each QOL domain. The inflammatory pathway has the strongest evidence as a controlling mechanism underlying fatigue. Inflammation and neurotransmission are key processes involved in pain perception and the COMT gene is associated with multiple sorts of pain. The neurotransmitter and neuroplasticity theories have the strongest evidence for their relationship with depression. Oxytocin-related genes and genes involved in the serotonergic and dopaminergic pathways play a role in social functioning. Inflammatory pathways, via cytokines, also play an important role in overall QOL. Conclusions Whereas the current findings need future experiments and replication efforts, they will provide researchers supportive background information when embarking on studies relating candidate genes and/or molecular markers to QOL domains. The ultimate goal of this area of research is to enhance patients’ QOL. PMID:24604075

Horizontal gene transfer in silkworm, Bombyx mori

PubMed Central

2011-01-01

Background The domesticated silkworm, Bombyx mori, is the model insect for the order Lepidoptera, has economically important values, and has gained some representative behavioral characteristics compared to its wild ancestor. The genome of B. mori has been fully sequenced while function analysis of BmChi-h and BmSuc1 genes revealed that horizontal gene transfer (HGT) maybe bestow a clear selective advantage to B. mori. However, the role of HGT in the evolutionary history of B. mori is largely unexplored. In this study, we compare the whole genome of B. mori with those of 382 prokaryotic and eukaryotic species to investigate the potential HGTs. Results Ten candidate HGT events were defined in B. mori by comprehensive sequence analysis using Maximum Likelihood and Bayesian method combining with EST checking. Phylogenetic analysis of the candidate HGT genes suggested that one HGT was plant-to- B. mori transfer while nine were bacteria-to- B. mori transfer. Furthermore, functional analysis based on expression, coexpression and related literature searching revealed that several HGT candidate genes have added important characters, such as resistance to pathogen, to B. mori. Conclusions Results from this study clearly demonstrated that HGTs play an important role in the evolution of B. mori although the number of HGT events in B. mori is in general smaller than those of microbes and other insects. In particular, interdomain HGTs in B. mori may give rise to functional, persistent, and possibly evolutionarily significant new genes. PMID:21595916

New mutations in BBS genes in small consanguineous families with Bardet-Biedl syndrome: Detection of candidate regions by homozygosity mapping

PubMed Central

Pereiro, Ines; Piñeiro-Gallego, Teresa; Baiget, Montserrat; Borrego, Salud; Ayuso, Carmen; Searby, Charles; Nishimura, Darryl

2010-01-01

Purpose Bardet-Biedl syndrome (BBS, OMIM 209900) is a rare multi-organ disorder in which BBS patients manifest a variable phenotype that includes retinal dystrophy, polydactyly, mental delay, obesity, and also reproductive tract and renal abnormalities. Mutations in 14 genes (BBS1–BBS14) are found in 70% of the patients, indicating that additional mutations in known and new BBS genes remain to be identified. Therefore, the molecular diagnosis of this complex disorder is a challenging task. Methods In this study we show the use of the genome-wide homozygosity mapping strategy in the mutation detection of nine Caucasian BBS families, eight of them consanguineous and one from the same geographic area with no proven consanguinity. Results We identified the disease-causing mutation in six of the families studied, five of which had novel sequence variants in BBS3, BBS6, and BBS12. This is the first null mutation reported in BBS3. Furthermore, this approach defined homozygous candidate regions that could harbor potential candidate genes for BBS in three of the families. Conclusions These findings further underline the importance of homozygosity mapping as a useful technology for diagnosis in small consanguineous families with a complex disease like BBS. PMID:20142850

Using Zebrafish to Test the Genetic Basis of Human Craniofacial Diseases.

PubMed

Machado, R Grecco; Eames, B Frank

2017-10-01

Genome-wide association studies (GWASs) opened an innovative and productive avenue to investigate the molecular basis of human craniofacial disease. However, GWASs identify candidate genes only; they do not prove that any particular one is the functional villain underlying disease or just an unlucky genomic bystander. Genetic manipulation of animal models is the best approach to reveal which genetic loci identified from human GWASs are functionally related to specific diseases. The purpose of this review is to discuss the potential of zebrafish to resolve which candidate genetic loci are mechanistic drivers of craniofacial diseases. Many anatomic, embryonic, and genetic features of craniofacial development are conserved among zebrafish and mammals, making zebrafish a good model of craniofacial diseases. Also, the ability to manipulate gene function in zebrafish was greatly expanded over the past 20 y, enabling systems such as Gateway Tol2 and CRISPR-Cas9 to test gain- and loss-of-function alleles identified from human GWASs in coding and noncoding regions of DNA. With the optimization of genetic editing methods, large numbers of candidate genes can be efficiently interrogated. Finding the functional villains that underlie diseases will permit new treatments and prevention strategies and will increase understanding of how gene pathways operate during normal development.

Using whole-exome sequencing to identify variants inherited from mosaic parents

PubMed Central

Rios, Jonathan J; Delgado, Mauricio R

2015-01-01

Whole-exome sequencing (WES) has allowed the discovery of genes and variants causing rare human disease. This is often achieved by comparing nonsynonymous variants between unrelated patients, and particularly for sporadic or recessive disease, often identifies a single or few candidate genes for further consideration. However, despite the potential for this approach to elucidate the genetic cause of rare human disease, a majority of patients fail to realize a genetic diagnosis using standard exome analysis methods. Although genetic heterogeneity contributes to the difficulty of exome sequence analysis between patients, it remains plausible that rare human disease is not caused by de novo or recessive variants. Multiple human disorders have been described for which the variant was inherited from a phenotypically normal mosaic parent. Here we highlight the potential for exome sequencing to identify a reasonable number of candidate genes when dominant disease variants are inherited from a mosaic parent. We show the power of WES to identify a limited number of candidate genes using this disease model and how sequence coverage affects identification of mosaic variants by WES. We propose this analysis as an alternative to discover genetic causes of rare human disorders for which typical WES approaches fail to identify likely pathogenic variants. PMID:24986828

QTL Mapping and CRISPR/Cas9 Editing to Identify a Drug Resistance Gene in Toxoplasma gondii.

PubMed

Shen, Bang; Powell, Robin H; Behnke, Michael S

2017-06-22

Scientific knowledge is intrinsically linked to available technologies and methods. This article will present two methods that allowed for the identification and verification of a drug resistance gene in the Apicomplexan parasite Toxoplasma gondii, the method of Quantitative Trait Locus (QTL) mapping using a Whole Genome Sequence (WGS) -based genetic map and the method of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 -based gene editing. The approach of QTL mapping allows one to test if there is a correlation between a genomic region(s) and a phenotype. Two datasets are required to run a QTL scan, a genetic map based on the progeny of a recombinant cross and a quantifiable phenotype assessed in each of the progeny of that cross. These datasets are then formatted to be compatible with R/qtl software that generates a QTL scan to identify significant loci correlated with the phenotype. Although this can greatly narrow the search window of possible candidates, QTLs span regions containing a number of genes from which the causal gene needs to be identified. Having WGS of the progeny was critical to identify the causal drug resistance mutation at the gene level. Once identified, the candidate mutation can be verified by genetic manipulation of drug sensitive parasites. The most facile and efficient method to genetically modify T. gondii is the CRISPR/Cas9 system. This system comprised of just 2 components both encoded on a single plasmid, a single guide RNA (gRNA) containing a 20 bp sequence complementary to the genomic target and the Cas9 endonuclease that generates a double-strand DNA break (DSB) at the target, repair of which allows for insertion or deletion of sequences around the break site. This article provides detailed protocols to use CRISPR/Cas9 based genome editing tools to verify the gene responsible for sinefungin resistance and to construct transgenic parasites.

QTL Mapping and CRISPR/Cas9 Editing to Identify a Drug Resistance Gene in Toxoplasma gondii

PubMed Central

Shen, Bang; Powell, Robin H.; Behnke, Michael S.

2017-01-01

Scientific knowledge is intrinsically linked to available technologies and methods. This article will present two methods that allowed for the identification and verification of a drug resistance gene in the Apicomplexan parasite Toxoplasma gondii, the method of Quantitative Trait Locus (QTL) mapping using a Whole Genome Sequence (WGS) -based genetic map and the method of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 -based gene editing. The approach of QTL mapping allows one to test if there is a correlation between a genomic region(s) and a phenotype. Two datasets are required to run a QTL scan, a genetic map based on the progeny of a recombinant cross and a quantifiable phenotype assessed in each of the progeny of that cross. These datasets are then formatted to be compatible with R/qtl software that generates a QTL scan to identify significant loci correlated with the phenotype. Although this can greatly narrow the search window of possible candidates, QTLs span regions containing a number of genes from which the causal gene needs to be identified. Having WGS of the progeny was critical to identify the causal drug resistance mutation at the gene level. Once identified, the candidate mutation can be verified by genetic manipulation of drug sensitive parasites. The most facile and efficient method to genetically modify T. gondii is the CRISPR/Cas9 system. This system comprised of just 2 components both encoded on a single plasmid, a single guide RNA (gRNA) containing a 20 bp sequence complementary to the genomic target and the Cas9 endonuclease that generates a double-strand DNA break (DSB) at the target, repair of which allows for insertion or deletion of sequences around the break site. This article provides detailed protocols to use CRISPR/Cas9 based genome editing tools to verify the gene responsible for sinefungin resistance and to construct transgenic parasites. PMID:28671645

Case-control approach application for finding a relationship between candidate genes and clinical mastitis in Holstein dairy cattle.

PubMed

Bagheri, Masoumeh; Moradi-Sharhrbabak, M; Miraie-Ashtiani, R; Safdari-Shahroudi, M; Abdollahi-Arpanahi, R

2016-02-01

Mastitis is a major source of economic loss in dairy herds. The objective of this research was to evaluate the association between genotypes within SLC11A1 and CXCR1 candidate genes and clinical mastitis in Holstein dairy cattle using the selective genotyping method. The data set contained clinical mastitis records of 3,823 Holstein cows from two Holstein dairy herds located in two different regions in Iran. Data included the number of cases of clinical mastitis per lactation. Selective genotyping was based on extreme values for clinical mastitis residuals (CMR) from mixed model analyses. Two extreme groups consisting of 135 cows were formed (as cases and controls), and genotyped for the two candidate genes, namely, SLC11A1 and CXCR1, using polymerase chain reaction-single strand conformation polymorphism (PCR-SSCP) and polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP), respectively. Associations between single nucleotide polymorphism (SNP) genotypes with CMR and breeding values for milk and protein yield were carried out by applying logistic regression analyses, i.e. estimating the probability of the heterogeneous genotype in the dependency of values for CMR and breeding values (BVs). The sequencing results revealed a novel mutation in 1139 bp of exon 11 of the SLC11A1 gene and this SNP had a significant association with CMR (P < 0.05). PCR-RFLP analysis leads to three banding patterns for CXCR1c.735C>G and these genotypes had significant relationships with CMR. Overall, the results showed that SLC11A1 and CXCR1 are valuable candidate genes for the improvement of mastitis resistance as well as production traits in dairy cattle populations.

Gene expression factor analysis to differentiate pathways linked to fibromyalgia, chronic fatigue syndrome, and depression in a diverse patient sample

PubMed Central

Iacob, Eli; Light, Alan R.; Donaldson, Gary W.; Okifuji, Akiko; Hughen, Ronald W.; White, Andrea T.; Light, Kathleen C.

2015-01-01

Objective To determine if independent candidate genes can be grouped into meaningful biological factors and if these factors are associated with the diagnosis of chronic fatigue syndrome (CFS) and fibromyalgia (FMS) while controlling for co-morbid depression, sex, and age. Methods We included leukocyte mRNA gene expression from a total of 261 individuals including healthy controls (n=61), patients with FMS only (n=15), CFS only (n=33), co-morbid CFS and FMS (n=79), and medication-resistant (n=42) or medication-responsive (n=31) depression. We used Exploratory Factor Analysis (EFA) on 34 candidate genes to determine factor scores and regression analysis to examine if these factors were associated with specific diagnoses. Results EFA resulted in four independent factors with minimal overlap of genes between factors explaining 51% of the variance. We labeled these factors by function as: 1) Purinergic and cellular modulators; 2) Neuronal growth and immune function; 3) Nociception and stress mediators; 4) Energy and mitochondrial function. Regression analysis predicting these biological factors using FMS, CFS, depression severity, age, and sex revealed that greater expression in Factors 1 and 3 was positively associated with CFS and negatively associated with depression severity (QIDS score), but not associated with FMS. Conclusion Expression of candidate genes can be grouped into meaningful clusters, and CFS and depression are associated with the same 2 clusters but in opposite directions when controlling for co-morbid FMS. Given high co-morbid disease and interrelationships between biomarkers, EFA may help determine patient subgroups in this population based on gene expression. PMID:26097208

Survival dimensionality reduction (SDR): development and clinical application of an innovative approach to detect epistasis in presence of right-censored data

PubMed Central

2010-01-01

Background Epistasis is recognized as a fundamental part of the genetic architecture of individuals. Several computational approaches have been developed to model gene-gene interactions in case-control studies, however, none of them is suitable for time-dependent analysis. Herein we introduce the Survival Dimensionality Reduction (SDR) algorithm, a non-parametric method specifically designed to detect epistasis in lifetime datasets. Results The algorithm requires neither specification about the underlying survival distribution nor about the underlying interaction model and proved satisfactorily powerful to detect a set of causative genes in synthetic epistatic lifetime datasets with a limited number of samples and high degree of right-censorship (up to 70%). The SDR method was then applied to a series of 386 Dutch patients with active rheumatoid arthritis that were treated with anti-TNF biological agents. Among a set of 39 candidate genes, none of which showed a detectable marginal effect on anti-TNF responses, the SDR algorithm did find that the rs1801274 SNP in the FcγRIIa gene and the rs10954213 SNP in the IRF5 gene non-linearly interact to predict clinical remission after anti-TNF biologicals. Conclusions Simulation studies and application in a real-world setting support the capability of the SDR algorithm to model epistatic interactions in candidate-genes studies in presence of right-censored data. Availability: http://sourceforge.net/projects/sdrproject/ PMID:20691091

Inheritance-mode specific pathogenicity prioritization (ISPP) for human protein coding genes.

PubMed

Hsu, Jacob Shujui; Kwan, Johnny S H; Pan, Zhicheng; Garcia-Barcelo, Maria-Mercè; Sham, Pak Chung; Li, Miaoxin

2016-10-15

Exome sequencing studies have facilitated the detection of causal genetic variants in yet-unsolved Mendelian diseases. However, the identification of disease causal genes among a list of candidates in an exome sequencing study is still not fully settled, and it is often difficult to prioritize candidate genes for follow-up studies. The inheritance mode provides crucial information for understanding Mendelian diseases, but none of the existing gene prioritization tools fully utilize this information. We examined the characteristics of Mendelian disease genes under different inheritance modes. The results suggest that Mendelian disease genes with autosomal dominant (AD) inheritance mode are more haploinsufficiency and de novo mutation sensitive, whereas those autosomal recessive (AR) genes have significantly more non-synonymous variants and regulatory transcript isoforms. In addition, the X-linked (XL) Mendelian disease genes have fewer non-synonymous and synonymous variants. As a result, we derived a new scoring system for prioritizing candidate genes for Mendelian diseases according to the inheritance mode. Our scoring system assigned to each annotated protein-coding gene (N = 18 859) three pathogenic scores according to the inheritance mode (AD, AR and XL). This inheritance mode-specific framework achieved higher accuracy (area under curve  = 0.84) in XL mode. The inheritance-mode specific pathogenicity prioritization (ISPP) outperformed other well-known methods including Haploinsufficiency, Recessive, Network centrality, Genic Intolerance, Gene Damage Index and Gene Constraint scores. This systematic study suggests that genes manifesting disease inheritance modes tend to have unique characteristics. ISPP is included in KGGSeq v1.0 (http://grass.cgs.hku.hk/limx/kggseq/), and source code is available from (https://github.com/jacobhsu35/ISPP.git). mxli@hku.hkSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

The CanOE strategy: integrating genomic and metabolic contexts across multiple prokaryote genomes to find candidate genes for orphan enzymes.

PubMed

Smith, Adam Alexander Thil; Belda, Eugeni; Viari, Alain; Medigue, Claudine; Vallenet, David

2012-05-01

Of all biochemically characterized metabolic reactions formalized by the IUBMB, over one out of four have yet to be associated with a nucleic or protein sequence, i.e. are sequence-orphan enzymatic activities. Few bioinformatics annotation tools are able to propose candidate genes for such activities by exploiting context-dependent rather than sequence-dependent data, and none are readily accessible and propose result integration across multiple genomes. Here, we present CanOE (Candidate genes for Orphan Enzymes), a four-step bioinformatics strategy that proposes ranked candidate genes for sequence-orphan enzymatic activities (or orphan enzymes for short). The first step locates "genomic metabolons", i.e. groups of co-localized genes coding proteins catalyzing reactions linked by shared metabolites, in one genome at a time. These metabolons can be particularly helpful for aiding bioanalysts to visualize relevant metabolic data. In the second step, they are used to generate candidate associations between un-annotated genes and gene-less reactions. The third step integrates these gene-reaction associations over several genomes using gene families, and summarizes the strength of family-reaction associations by several scores. In the final step, these scores are used to rank members of gene families which are proposed for metabolic reactions. These associations are of particular interest when the metabolic reaction is a sequence-orphan enzymatic activity. Our strategy found over 60,000 genomic metabolons in more than 1,000 prokaryote organisms from the MicroScope platform, generating candidate genes for many metabolic reactions, of which more than 70 distinct orphan reactions. A computational validation of the approach is discussed. Finally, we present a case study on the anaerobic allantoin degradation pathway in Escherichia coli K-12.

Transcriptome analysis of Brassica napus pod using RNA-Seq and identification of lipid-related candidate genes.

PubMed

Xu, Hai-Ming; Kong, Xiang-Dong; Chen, Fei; Huang, Ji-Xiang; Lou, Xiang-Yang; Zhao, Jian-Yi

2015-10-24

Brassica napus is an important oilseed crop. Dissection of the genetic architecture underlying oil-related biological processes will greatly facilitates the genetic improvement of rapeseed. The differential gene expression during pod development offers a snapshot on the genes responsible for oil accumulation in. To identify candidate genes in the linkage peaks reported previously, we used RNA sequencing (RNA-Seq) technology to analyze the pod transcriptomes of German cultivar Sollux and Chinese inbred line Gaoyou. The RNA samples were collected for RNA-Seq at 5-7, 15-17 and 25-27 days after flowering (DAF). Bioinformatics analysis was performed to investigate differentially expressed genes (DEGs). Gene annotation analysis was integrated with QTL mapping and Brassica napus pod transcriptome profiling to detect potential candidate genes in oilseed. Four hundred sixty five and two thousand, one hundred fourteen candidate DEGs were identified, respectively, between two varieties at the same stages and across different periods of each variety. Then, 33 DEGs between Sollux and Gaoyou were identified as the candidate genes affecting seed oil content by combining those DEGs with the quantitative trait locus (QTL) mapping results, of which, one was found to be homologous to Arabidopsis thaliana lipid-related genes. Intervarietal DEGs of lipid pathways in QTL regions represent important candidate genes for oil-related traits. Integrated analysis of transcriptome profiling, QTL mapping and comparative genomics with other relative species leads to efficient identification of most plausible functional genes underlying oil-content related characters, offering valuable resources for bettering breeding program of Brassica napus. This study provided a comprehensive overview on the pod transcriptomes of two varieties with different oil-contents at the three developmental stages.

Endeavour update: a web resource for gene prioritization in multiple species

PubMed Central

Tranchevent, Léon-Charles; Barriot, Roland; Yu, Shi; Van Vooren, Steven; Van Loo, Peter; Coessens, Bert; De Moor, Bart; Aerts, Stein; Moreau, Yves

2008-01-01

Endeavour (http://www.esat.kuleuven.be/endeavourweb; this web site is free and open to all users and there is no login requirement) is a web resource for the prioritization of candidate genes. Using a training set of genes known to be involved in a biological process of interest, our approach consists of (i) inferring several models (based on various genomic data sources), (ii) applying each model to the candidate genes to rank those candidates against the profile of the known genes and (iii) merging the several rankings into a global ranking of the candidate genes. In the present article, we describe the latest developments of Endeavour. First, we provide a web-based user interface, besides our Java client, to make Endeavour more universally accessible. Second, we support multiple species: in addition to Homo sapiens, we now provide gene prioritization for three major model organisms: Mus musculus, Rattus norvegicus and Caenorhabditis elegans. Third, Endeavour makes use of additional data sources and is now including numerous databases: ontologies and annotations, protein–protein interactions, cis-regulatory information, gene expression data sets, sequence information and text-mining data. We tested the novel version of Endeavour on 32 recent disease gene associations from the literature. Additionally, we describe a number of recent independent studies that made use of Endeavour to prioritize candidate genes for obesity and Type II diabetes, cleft lip and cleft palate, and pulmonary fibrosis. PMID:18508807

Development of a rapid and simple Agrobacterium tumefaciens mediated transformation system for the fungal pathogen Heterobasidion annosum

Treesearch

Nicklas Samils; Malin Elfstrand; Daniel L. Lindner Czederpiltz; Jan Fahleson; Ake Olson; Christina Dixelius; Jan Stenlid

2006-01-01

Heterobasidion annosum causes root and butt-rot in trees and is the most serious forest pathogen in the northern hemisphere. We developed a rapid and simple Agrobacterium-mediated method of gene delivery into H. annosum to be used in functional studies of candidate genes and for visualization of mycelial interactions. Heterobasidion annosum TC 32-1 was cocultivated at...

Identification and Comparison of Candidate Olfactory Genes in the Olfactory and Non-Olfactory Organs of Elm Pest Ambrostoma quadriimpressum (Coleoptera: Chrysomelidae) Based on Transcriptome Analysis.

PubMed

Wang, Yinliang; Chen, Qi; Zhao, Hanbo; Ren, Bingzhong

2016-01-01

The leaf beetle Ambrostoma quadriimpressum (Coleoptera: Chrysomelidae) is a predominant forest pest that causes substantial damage to the lumber industry and city management. However, no effective and environmentally friendly chemical method has been discovered to control this pest. Until recently, the molecular basis of the olfactory system in A. quadriimpressum was completely unknown. In this study, antennae and leg transcriptomes were analyzed and compared using deep sequencing data to identify the olfactory genes in A. quadriimpressum. Moreover, the expression profiles of both male and female candidate olfactory genes were analyzed and validated by bioinformatics, motif analysis, homology analysis, semi-quantitative RT-PCR and RT-qPCR experiments in antennal and non-olfactory organs to explore the candidate olfactory genes that might play key roles in the life cycle of A. quadriimpressum. As a result, approximately 102.9 million and 97.3 million clean reads were obtained from the libraries created from the antennas and legs, respectively. Annotation led to 34344 Unigenes, which were matched to known proteins. Annotation data revealed that the number of genes in antenna with binding functions and receptor activity was greater than that of legs. Furthermore, many pathway genes were differentially expressed in the two organs. Sixteen candidate odorant binding proteins (OBPs), 10 chemosensory proteins (CSPs), 34 odorant receptors (ORs), 20 inotropic receptors [1] and 2 sensory neuron membrane proteins (SNMPs) and their isoforms were identified. Additionally, 15 OBPs, 9 CSPs, 18 ORs, 6 IRs and 2 SNMPs were predicted to be complete ORFs. Using RT-PCR, RT-qPCR and homology analysis, AquaOBP1/2/4/7/C1/C6, AquaCSP3/9, AquaOR8/9/10/14/15/18/20/26/29/33, AquaIR8a/13/25a showed olfactory-specific expression, indicating that these genes might play a key role in olfaction-related behaviors in A. quadriimpressum such as foraging and seeking. AquaOBP4/C5, AquaOBP4/C5, AquaCSP7/9/10, AquaOR17/24/32 and AquaIR4 were highly expressed in the antenna of males, suggesting that these genes were related to sex-specific behaviors, and expression trends that were male specific were observed for most candidate olfactory genes, which supported the existence of a female-produced sex pheromone in A. quadriimpressum. All of these results could provide valuable information and guidance for future functional studies on these genes and provide better molecular knowledge regarding the olfactory system in A. quadriimpressum.

Integrative strategies to identify candidate genes in rodent models of human alcoholism.

PubMed

Treadwell, Julie A

2006-01-01

The search for genes underlying alcohol-related behaviours in rodent models of human alcoholism has been ongoing for many years with only limited success. Recently, new strategies that integrate several of the traditional approaches have provided new insights into the molecular mechanisms underlying ethanol's actions in the brain. We have used alcohol-preferring C57BL/6J (B6) and alcohol-avoiding DBA/2J (D2) genetic strains of mice in an integrative strategy combining high-throughput gene expression screening, genetic segregation analysis, and mapping to previously published quantitative trait loci to uncover candidate genes for the ethanol-preference phenotype. In our study, 2 genes, retinaldehyde binding protein 1 (Rlbp1) and syntaxin 12 (Stx12), were found to be strong candidates for ethanol preference. Such experimental approaches have the power and the potential to greatly speed up the laborious process of identifying candidate genes for the animal models of human alcoholism.

LOD score exclusion analyses for candidate genes using random population samples.

PubMed

Deng, H W; Li, J; Recker, R R

2001-05-01

While extensive analyses have been conducted to test for, no formal analyses have been conducted to test against, the importance of candidate genes with random population samples. We develop a LOD score approach for exclusion analyses of candidate genes with random population samples. Under this approach, specific genetic effects and inheritance models at candidate genes can be analysed and if a LOD score is < or = - 2.0, the locus can be excluded from having an effect larger than that specified. Computer simulations show that, with sample sizes often employed in association studies, this approach has high power to exclude a gene from having moderate genetic effects. In contrast to regular association analyses, population admixture will not affect the robustness of our analyses; in fact, it renders our analyses more conservative and thus any significant exclusion result is robust. Our exclusion analysis complements association analysis for candidate genes in random population samples and is parallel to the exclusion mapping analyses that may be conducted in linkage analyses with pedigrees or relative pairs. The usefulness of the approach is demonstrated by an application to test the importance of vitamin D receptor and estrogen receptor genes underlying the differential risk to osteoporotic fractures.

Demographically-Based Evaluation of Genomic Regions under Selection in Domestic Dogs

PubMed Central

Freedman, Adam H.; Schweizer, Rena M.; Ortega-Del Vecchyo, Diego; Han, Eunjung; Davis, Brian W.; Gronau, Ilan; Silva, Pedro M.; Galaverni, Marco; Fan, Zhenxin; Marx, Peter; Lorente-Galdos, Belen; Ramirez, Oscar; Hormozdiari, Farhad; Alkan, Can; Vilà, Carles; Squire, Kevin; Geffen, Eli; Kusak, Josip; Boyko, Adam R.; Parker, Heidi G.; Lee, Clarence; Tadigotla, Vasisht; Siepel, Adam; Bustamante, Carlos D.; Harkins, Timothy T.; Nelson, Stanley F.; Marques-Bonet, Tomas; Ostrander, Elaine A.; Wayne, Robert K.; Novembre, John

2016-01-01

Controlling for background demographic effects is important for accurately identifying loci that have recently undergone positive selection. To date, the effects of demography have not yet been explicitly considered when identifying loci under selection during dog domestication. To investigate positive selection on the dog lineage early in the domestication, we examined patterns of polymorphism in six canid genomes that were previously used to infer a demographic model of dog domestication. Using an inferred demographic model, we computed false discovery rates (FDR) and identified 349 outlier regions consistent with positive selection at a low FDR. The signals in the top 100 regions were frequently centered on candidate genes related to brain function and behavior, including LHFPL3, CADM2, GRIK3, SH3GL2, MBP, PDE7B, NTAN1, and GLRA1. These regions contained significant enrichments in behavioral ontology categories. The 3rd top hit, CCRN4L, plays a major role in lipid metabolism, that is supported by additional metabolism related candidates revealed in our scan, including SCP2D1 and PDXC1. Comparing our method to an empirical outlier approach that does not directly account for demography, we found only modest overlaps between the two methods, with 60% of empirical outliers having no overlap with our demography-based outlier detection approach. Demography-aware approaches have lower-rates of false discovery. Our top candidates for selection, in addition to expanding the set of neurobehavioral candidate genes, include genes related to lipid metabolism, suggesting a dietary target of selection that was important during the period when proto-dogs hunted and fed alongside hunter-gatherers. PMID:26943675

Application of selection mapping to identify genomic regions associated with dairy production in sheep.

PubMed

Gutiérrez-Gil, Beatriz; Arranz, Juan Jose; Pong-Wong, Ricardo; García-Gámez, Elsa; Kijas, James; Wiener, Pamela

2014-01-01

In Europe, especially in Mediterranean areas, the sheep has been traditionally exploited as a dual purpose species, with income from both meat and milk. Modernization of husbandry methods and the establishment of breeding schemes focused on milk production have led to the development of "dairy breeds." This study investigated selective sweeps specifically related to dairy production in sheep by searching for regions commonly identified in different European dairy breeds. With this aim, genotypes from 44,545 SNP markers covering the sheep autosomes were analysed in both European dairy and non-dairy sheep breeds using two approaches: (i) identification of genomic regions showing extreme genetic differentiation between each dairy breed and a closely related non-dairy breed, and (ii) identification of regions with reduced variation (heterozygosity) in the dairy breeds using two methods. Regions detected in at least two breeds (breed pairs) by the two approaches (genetic differentiation and at least one of the heterozygosity-based analyses) were labeled as core candidate convergence regions and further investigated for candidate genes. Following this approach six regions were detected. For some of them, strong candidate genes have been proposed (e.g. ABCG2, SPP1), whereas some other genes designated as candidates based on their association with sheep and cattle dairy traits (e.g. LALBA, DGAT1A) were not associated with a detectable sweep signal. Few of the identified regions were coincident with QTL previously reported in sheep, although many of them corresponded to orthologous regions in cattle where QTL for dairy traits have been identified. Due to the limited number of QTL studies reported in sheep compared with cattle, the results illustrate the potential value of selection mapping to identify genomic regions associated with dairy traits in sheep.

Application of Selection Mapping to Identify Genomic Regions Associated with Dairy Production in Sheep

PubMed Central

Gutiérrez-Gil, Beatriz; Arranz, Juan Jose; Pong-Wong, Ricardo; García-Gámez, Elsa; Kijas, James; Wiener, Pamela

2014-01-01

In Europe, especially in Mediterranean areas, the sheep has been traditionally exploited as a dual purpose species, with income from both meat and milk. Modernization of husbandry methods and the establishment of breeding schemes focused on milk production have led to the development of “dairy breeds.” This study investigated selective sweeps specifically related to dairy production in sheep by searching for regions commonly identified in different European dairy breeds. With this aim, genotypes from 44,545 SNP markers covering the sheep autosomes were analysed in both European dairy and non-dairy sheep breeds using two approaches: (i) identification of genomic regions showing extreme genetic differentiation between each dairy breed and a closely related non-dairy breed, and (ii) identification of regions with reduced variation (heterozygosity) in the dairy breeds using two methods. Regions detected in at least two breeds (breed pairs) by the two approaches (genetic differentiation and at least one of the heterozygosity-based analyses) were labeled as core candidate convergence regions and further investigated for candidate genes. Following this approach six regions were detected. For some of them, strong candidate genes have been proposed (e.g. ABCG2, SPP1), whereas some other genes designated as candidates based on their association with sheep and cattle dairy traits (e.g. LALBA, DGAT1A) were not associated with a detectable sweep signal. Few of the identified regions were coincident with QTL previously reported in sheep, although many of them corresponded to orthologous regions in cattle where QTL for dairy traits have been identified. Due to the limited number of QTL studies reported in sheep compared with cattle, the results illustrate the potential value of selection mapping to identify genomic regions associated with dairy traits in sheep. PMID:24788864

Examination of AVPR1a as an autism susceptibility gene.

PubMed

Wassink, T H; Piven, J; Vieland, V J; Pietila, J; Goedken, R J; Folstein, S E; Sheffield, V C

2004-10-01

Impaired reciprocal social interaction is one of the core features of autism. While its determinants are complex, one biomolecular pathway that clearly influences social behavior is the arginine-vasopressin (AVP) system. The behavioral effects of AVP are mediated through the AVP receptor 1a (AVPR1a), making the AVPR1a gene a reasonable candidate for autism susceptibility. We tested the gene's contribution to autism by screening its exons in 125 independent autistic probands and genotyping two promoter polymorphisms in 65 autism affected sibling pair (ASP) families. While we found no nonconservative coding sequence changes, we did identify evidence of linkage and of linkage disequilibrium. These results were most pronounced in a subset of the ASP families with relatively less severe impairment of language. Thus, though we did not demonstrate a disease-causing variant in the coding sequence, numerous nontraditional disease-causing genetic abnormalities are known to exist that would escape detection by traditional gene screening methods. Given the emerging biological, animal model, and now genetic data, AVPR1a and genes in the AVP system remain strong candidates for involvement in autism susceptibility and deserve continued scrutiny.

Mutant prenyltransferase-like mitochondrial protein (PLMP) and mitochondrial abnormalities in kd/kd mice

PubMed Central

Peng, Min; Jarett, Leonard; Meade, Ray; Madaio, Michael P.; Hancock, Wayne W.; George, Alfred L.; Neilson, Eric G.; Gasser, David L.

2008-01-01

Background Mice that are homozygous for the kidney disease (kd) mutation are apparently healthy for the first 8 weeks of life, but spontaneously develop a severe form of interstitial nephritis that progresses to end-stage renal disease (ESRD) by 4 to 8 months of age. By testing for linkage to microsatellite markers, we previously localized the kd gene to a YAC/BAC contig. Methods The sequence of the entire critical region was examined, and candidate genes were identified. These candidate genes were sequenced in both mutant (kd/kd) mice and normal controls. The phenotype was further characterized by immunohistochemistry and electron microscopy. Transgenic mice were constructed that carried the wild-type allele of the prime candidate gene, and this transgene was transferred to a kd/kd background by breeding. Results We have obtained evidence that kd is a mutant allele of a novel gene for a prenyltransferase-like mitochondrial protein (PLMP). This gene is alternatively spliced, with the larger gene product having one domain that resembles transprenyltransferase and another that is similar to geranylgeranyl pyrophosphate synthase. The smaller gene product includes only the first domain. An antiserum to PLMP localizes to mitochondria, and ultrastructural defects are present in the mitochondria of renal tubular epithelial cells, and to a lesser extent, hepatocytes and heart cells from kd/kd mice. In a line of kd/kd mice that carried the wild-type PLMP allele as a transgene, only 1 out of 13 animals expressed the disease by 120 days of age. Conclusion The kd allele codes for a novel protein that localizes to the mitochondria, and the kd/kd mouse has dysmorphic mitochondria in the renal tubular epithelial cells. This mouse is therefore a unique animal model for studying mechanisms that lead to tubulointerstitial nephritis. PMID:15200409

Evolutionary transgenomics: prospects and challenges.

PubMed

Correa, Raul; Baum, David A

2015-01-01

Many advances in our understanding of the genetic basis of species differences have arisen from transformation experiments, which allow us to study the effect of genes from one species (the donor) when placed in the genetic background of another species (the recipient). Such interspecies transformation experiments are usually focused on candidate genes - genes that, based on work in model systems, are suspected to be responsible for certain phenotypic differences between the donor and recipient species. We suggest that the high efficiency of transformation in a few plant species, most notably Arabidopsis thaliana, combined with the small size of typical plant genes and their cis-regulatory regions allow implementation of a screening strategy that does not depend upon a priori candidate gene identification. This approach, transgenomics, entails moving many large genomic inserts of a donor species into the wild type background of a recipient species and then screening for dominant phenotypic effects. As a proof of concept, we recently conducted a transgenomic screen that analyzed more than 1100 random, large genomic inserts of the Alabama gladecress Leavenworthia alabamica for dominant phenotypic effects in the A. thaliana background. This screen identified one insert that shortens fruit and decreases A. thaliana fertility. In this paper we discuss the principles of transgenomic screens and suggest methods to help minimize the frequencies of false positive and false negative results. We argue that, because transgenomics avoids committing in advance to candidate genes it has the potential to help us identify truly novel genes or cryptic functions of known genes. Given the valuable knowledge that is likely to be gained, we believe the time is ripe for the plant evolutionary community to invest in transgenomic screens, at least in the mustard family Brassicaceae where many species are amenable to efficient transformation.

Phenoscape: Identifying Candidate Genes for Evolutionary Phenotypes

PubMed Central

Edmunds, Richard C.; Su, Baofeng; Balhoff, James P.; Eames, B. Frank; Dahdul, Wasila M.; Lapp, Hilmar; Lundberg, John G.; Vision, Todd J.; Dunham, Rex A.; Mabee, Paula M.; Westerfield, Monte

2016-01-01

Phenotypes resulting from mutations in genetic model organisms can help reveal candidate genes for evolutionarily important phenotypic changes in related taxa. Although testing candidate gene hypotheses experimentally in nonmodel organisms is typically difficult, ontology-driven information systems can help generate testable hypotheses about developmental processes in experimentally tractable organisms. Here, we tested candidate gene hypotheses suggested by expert use of the Phenoscape Knowledgebase, specifically looking for genes that are candidates responsible for evolutionarily interesting phenotypes in the ostariophysan fishes that bear resemblance to mutant phenotypes in zebrafish. For this, we searched ZFIN for genetic perturbations that result in either loss of basihyal element or loss of scales phenotypes, because these are the ancestral phenotypes observed in catfishes (Siluriformes). We tested the identified candidate genes by examining their endogenous expression patterns in the channel catfish, Ictalurus punctatus. The experimental results were consistent with the hypotheses that these features evolved through disruption in developmental pathways at, or upstream of, brpf1 and eda/edar for the ancestral losses of basihyal element and scales, respectively. These results demonstrate that ontological annotations of the phenotypic effects of genetic alterations in model organisms, when aggregated within a knowledgebase, can be used effectively to generate testable, and useful, hypotheses about evolutionary changes in morphology. PMID:26500251

Integration of QTL and bioinformatic tools to identify candidate genes for triglycerides in mice[S

PubMed Central

Leduc, Magalie S.; Hageman, Rachael S.; Verdugo, Ricardo A.; Tsaih, Shirng-Wern; Walsh, Kenneth; Churchill, Gary A.; Paigen, Beverly

2011-01-01

To identify genetic loci influencing lipid levels, we performed quantitative trait loci (QTL) analysis between inbred mouse strains MRL/MpJ and SM/J, measuring triglyceride levels at 8 weeks of age in F2 mice fed a chow diet. We identified one significant QTL on chromosome (Chr) 15 and three suggestive QTL on Chrs 2, 7, and 17. We also carried out microarray analysis on the livers of parental strains of 282 F2 mice and used these data to find cis-regulated expression QTL. We then narrowed the list of candidate genes under significant QTL using a “toolbox” of bioinformatic resources, including haplotype analysis; parental strain comparison for gene expression differences and nonsynonymous coding single nucleotide polymorphisms (SNP); cis-regulated eQTL in livers of F2 mice; correlation between gene expression and phenotype; and conditioning of expression on the phenotype. We suggest Slc25a7 as a candidate gene for the Chr 7 QTL and, based on expression differences, five genes (Polr3 h, Cyp2d22, Cyp2d26, Tspo, and Ttll12) as candidate genes for Chr 15 QTL. This study shows how bioinformatics can be used effectively to reduce candidate gene lists for QTL related to complex traits. PMID:21622629

Meta-Analysis of Tumor Stem-Like Breast Cancer Cells Using Gene Set and Network Analysis

PubMed Central

Lee, Won Jun; Kim, Sang Cheol; Yoon, Jung-Ho; Yoon, Sang Jun; Lim, Johan; Kim, You-Sun; Kwon, Sung Won; Park, Jeong Hill

2016-01-01

Generally, cancer stem cells have epithelial-to-mesenchymal-transition characteristics and other aggressive properties that cause metastasis. However, there have been no confident markers for the identification of cancer stem cells and comparative methods examining adherent and sphere cells are widely used to investigate mechanism underlying cancer stem cells, because sphere cells have been known to maintain cancer stem cell characteristics. In this study, we conducted a meta-analysis that combined gene expression profiles from several studies that utilized tumorsphere technology to investigate tumor stem-like breast cancer cells. We used our own gene expression profiles along with the three different gene expression profiles from the Gene Expression Omnibus, which we combined using the ComBat method, and obtained significant gene sets using the gene set analysis of our datasets and the combined dataset. This experiment focused on four gene sets such as cytokine-cytokine receptor interaction that demonstrated significance in both datasets. Our observations demonstrated that among the genes of four significant gene sets, six genes were consistently up-regulated and satisfied the p-value of < 0.05, and our network analysis showed high connectivity in five genes. From these results, we established CXCR4, CXCL1 and HMGCS1, the intersecting genes of the datasets with high connectivity and p-value of < 0.05, as significant genes in the identification of cancer stem cells. Additional experiment using quantitative reverse transcription-polymerase chain reaction showed significant up-regulation in MCF-7 derived sphere cells and confirmed the importance of these three genes. Taken together, using meta-analysis that combines gene set and network analysis, we suggested CXCR4, CXCL1 and HMGCS1 as candidates involved in tumor stem-like breast cancer cells. Distinct from other meta-analysis, by using gene set analysis, we selected possible markers which can explain the biological mechanisms and suggested network analysis as an additional criterion for selecting candidates. PMID:26870956

In Silico Gene Prioritization by Integrating Multiple Data Sources

PubMed Central

Zhou, Yingyao; Shields, Robert; Chanda, Sumit K.; Elston, Robert C.; Li, Jing

2011-01-01

Identifying disease genes is crucial to the understanding of disease pathogenesis, and to the improvement of disease diagnosis and treatment. In recent years, many researchers have proposed approaches to prioritize candidate genes by considering the relationship of candidate genes and existing known disease genes, reflected in other data sources. In this paper, we propose an expandable framework for gene prioritization that can integrate multiple heterogeneous data sources by taking advantage of a unified graphic representation. Gene-gene relationships and gene-disease relationships are then defined based on the overall topology of each network using a diffusion kernel measure. These relationship measures are in turn normalized to derive an overall measure across all networks, which is utilized to rank all candidate genes. Based on the informativeness of available data sources with respect to each specific disease, we also propose an adaptive threshold score to select a small subset of candidate genes for further validation studies. We performed large scale cross-validation analysis on 110 disease families using three data sources. Results have shown that our approach consistently outperforms other two state of the art programs. A case study using Parkinson disease (PD) has identified four candidate genes (UBB, SEPT5, GPR37 and TH) that ranked higher than our adaptive threshold, all of which are involved in the PD pathway. In particular, a very recent study has observed a deletion of TH in a patient with PD, which supports the importance of the TH gene in PD pathogenesis. A web tool has been implemented to assist scientists in their genetic studies. PMID:21731658

Detecting Horizontal Gene Transfer between Closely Related Taxa

PubMed Central

Adato, Orit; Ninyo, Noga; Gophna, Uri; Snir, Sagi

2015-01-01

Horizontal gene transfer (HGT), the transfer of genetic material between organisms, is crucial for genetic innovation and the evolution of genome architecture. Existing HGT detection algorithms rely on a strong phylogenetic signal distinguishing the transferred sequence from ancestral (vertically derived) genes in its recipient genome. Detecting HGT between closely related species or strains is challenging, as the phylogenetic signal is usually weak and the nucleotide composition is normally nearly identical. Nevertheless, there is a great importance in detecting HGT between congeneric species or strains, especially in clinical microbiology, where understanding the emergence of new virulent and drug-resistant strains is crucial, and often time-sensitive. We developed a novel, self-contained technique named Near HGT, based on the synteny index, to measure the divergence of a gene from its native genomic environment and used it to identify candidate HGT events between closely related strains. The method confirms candidate transferred genes based on the constant relative mutability (CRM). Using CRM, the algorithm assigns a confidence score based on “unusual” sequence divergence. A gene exhibiting exceptional deviations according to both synteny and mutability criteria, is considered a validated HGT product. We first employed the technique to a set of three E. coli strains and detected several highly probable horizontally acquired genes. We then compared the method to existing HGT detection tools using a larger strain data set. When combined with additional approaches our new algorithm provides richer picture and brings us closer to the goal of detecting all newly acquired genes in a particular strain. PMID:26439115

Racial Differences in DNA-Methylation of CpG Sites Within Preterm-Promoting Genes and Gene Variants.

PubMed

Salihu, H M; Das, R; Morton, L; Huang, H; Paothong, A; Wilson, R E; Aliyu, M H; Salemi, J L; Marty, P J

2016-08-01

Objective To evaluate the role DNA methylation may play in genes associated with preterm birth for higher rates of preterm births in African-American women. Methods Fetal cord blood samples from births collected at delivery and maternal demographic and medical information were used in a cross-sectional study to examine fetal DNA methylation of genes implicated in preterm birth among black and non-black infants. Allele-specific DNA methylation analysis was performed using a methylation bead array. Targeted maximum likelihood estimation was applied to examine the relationship between race and fetal DNA methylation of candidate preterm birth genes. Receiver-operating characteristic analyses were then conducted to validate the CpG site methylation marker within the two racial groups. Bootstrapping, a method of validation and replication, was employed. Results 42 CpG sites were screened within 20 candidate gene variants reported consistently in the literature as being associated with preterm birth. Of these, three CpG sites on TNFAIP8 and PON1 genes (corresponding to: cg23917399; cg07086380; and cg07404485, respectively) were significantly differentially methylated between black and non-black individuals. The three CpG sites showed lower methylation status among infants of black women. Bootstrapping validated and replicated results. Conclusion for Practice Our study identified significant differences in levels of methylation on specific genes between black and non-black individuals. Understanding the genetic/epigenetic mechanisms that lead to preterm birth may lead to enhanced prevention strategies to reduce morbidity and mortality by eventually providing a means to identify individuals with a genetic predisposition to preterm labor.

The Genetic Basis for Variation in Sensitivity to Lead Toxicity in Drosophila melanogaster.

PubMed

Zhou, Shanshan; Morozova, Tatiana V; Hussain, Yasmeen N; Luoma, Sarah E; McCoy, Lenovia; Yamamoto, Akihiko; Mackay, Trudy F C; Anholt, Robert R H

2016-07-01

Lead toxicity presents a worldwide health problem, especially due to its adverse effects on cognitive development in children. However, identifying genes that give rise to individual variation in susceptibility to lead toxicity is challenging in human populations. Our goal was to use Drosophila melanogaster to identify evolutionarily conserved candidate genes associated with individual variation in susceptibility to lead exposure. To identify candidate genes associated with variation in susceptibility to lead toxicity, we measured effects of lead exposure on development time, viability and adult activity in the Drosophila melanogaster Genetic Reference Panel (DGRP) and performed genome-wide association analyses to identify candidate genes. We used mutants to assess functional causality of candidate genes and constructed a genetic network associated with variation in sensitivity to lead exposure, on which we could superimpose human orthologs. We found substantial heritabilities for all three traits and identified candidate genes associated with variation in susceptibility to lead exposure for each phenotype. The genetic architectures that determine variation in sensitivity to lead exposure are highly polygenic. Gene ontology and network analyses showed enrichment of genes associated with early development and function of the nervous system. Drosophila melanogaster presents an advantageous model to study the genetic underpinnings of variation in susceptibility to lead toxicity. Evolutionary conservation of cellular pathways that respond to toxic exposure allows predictions regarding orthologous genes and pathways across phyla. Thus, studies in the D. melanogaster model system can identify candidate susceptibility genes to guide subsequent studies in human populations. Zhou S, Morozova TV, Hussain YN, Luoma SE, McCoy L, Yamamoto A, Mackay TF, Anholt RR. 2016. The genetic basis for variation in sensitivity to lead toxicity in Drosophila melanogaster. Environ Health Perspect 124:1062-1070; http://dx.doi.org/10.1289/ehp.1510513.

Replication of type 2 diabetes candidate genes variations in three geographically unrelated Indian population groups.

PubMed

Ali, Shafat; Chopra, Rupali; Manvati, Siddharth; Singh, Yoginder Pal; Kaul, Nabodita; Behura, Anita; Mahajan, Ankit; Sehajpal, Prabodh; Gupta, Subash; Dhar, Manoj K; Chainy, Gagan B N; Bhanwer, Amarjit S; Sharma, Swarkar; Bamezai, Rameshwar N K

2013-01-01

Type 2 diabetes (T2D) is a syndrome of multiple metabolic disorders and is genetically heterogeneous. India comprises one of the largest global populations with highest number of reported type 2 diabetes cases. However, limited information about T2D associated loci is available for Indian populations. It is, therefore, pertinent to evaluate the previously associated candidates as well as identify novel genetic variations in Indian populations to understand the extent of genetic heterogeneity. We chose to do a cost effective high-throughput mass-array genotyping and studied the candidate gene variations associated with T2D in literature. In this case-control candidate genes association study, 91 SNPs from 55 candidate genes have been analyzed in three geographically independent population groups from India. We report the genetic variants in five candidate genes: TCF7L2, HHEX, ENPP1, IDE and FTO, are significantly associated (after Bonferroni correction, p<5.5E-04) with T2D susceptibility in combined population. Interestingly, SNP rs7903146 of the TCF7L2 gene passed the genome wide significance threshold (combined P value = 2.05E-08) in the studied populations. We also observed the association of rs7903146 with blood glucose (fasting and postprandial) levels, supporting the role of TCF7L2 gene in blood glucose homeostasis. Further, we noted that the moderate risk provided by the independently associated loci in combined population with Odds Ratio (OR)<1.38 increased to OR = 2.44, (95%CI = 1.67-3.59) when the risk providing genotypes of TCF7L2, HHEX, ENPP1 and FTO genes were combined, suggesting the importance of gene-gene interactions evaluation in complex disorders like T2D.

Replication of Type 2 Diabetes Candidate Genes Variations in Three Geographically Unrelated Indian Population Groups

PubMed Central

Ali, Shafat; Chopra, Rupali; Manvati, Siddharth; Mahajan, Ankit; Sehajpal, Prabodh; Gupta, Subash; Dhar, Manoj K.; Chainy, Gagan B. N.; Bhanwer, Amarjit S.; Sharma, Swarkar; Bamezai, Rameshwar N. K.

2013-01-01

Type 2 diabetes (T2D) is a syndrome of multiple metabolic disorders and is genetically heterogeneous. India comprises one of the largest global populations with highest number of reported type 2 diabetes cases. However, limited information about T2D associated loci is available for Indian populations. It is, therefore, pertinent to evaluate the previously associated candidates as well as identify novel genetic variations in Indian populations to understand the extent of genetic heterogeneity. We chose to do a cost effective high-throughput mass-array genotyping and studied the candidate gene variations associated with T2D in literature. In this case-control candidate genes association study, 91 SNPs from 55 candidate genes have been analyzed in three geographically independent population groups from India. We report the genetic variants in five candidate genes: TCF7L2, HHEX, ENPP1, IDE and FTO, are significantly associated (after Bonferroni correction, p<5.5E−04) with T2D susceptibility in combined population. Interestingly, SNP rs7903146 of the TCF7L2 gene passed the genome wide significance threshold (combined P value = 2.05E−08) in the studied populations. We also observed the association of rs7903146 with blood glucose (fasting and postprandial) levels, supporting the role of TCF7L2 gene in blood glucose homeostasis. Further, we noted that the moderate risk provided by the independently associated loci in combined population with Odds Ratio (OR)<1.38 increased to OR = 2.44, (95%CI = 1.67–3.59) when the risk providing genotypes of TCF7L2, HHEX, ENPP1 and FTO genes were combined, suggesting the importance of gene-gene interactions evaluation in complex disorders like T2D. PMID:23527042

Genetic basis of interindividual susceptibility to cancer cachexia: selection of potential candidate gene polymorphisms for association studies.

PubMed

Johns, N; Tan, B H; MacMillan, M; Solheim, T S; Ross, J A; Baracos, V E; Damaraju, S; Fearon, K C H

2014-12-01

Cancer cachexia is a complex and multifactorial disease. Evolving definitions highlight the fact that a diverse range of biological processes contribute to cancer cachexia. Part of the variation in who will and who will not develop cancer cachexia may be genetically determined. As new definitions, classifications and biological targets continue to evolve, there is a need for reappraisal of the literature for future candidate association studies. This review summarizes genes identified or implicated as well as putative candidate genes contributing to cachexia, identified through diverse technology platforms and model systems to further guide association studies. A systematic search covering 1986-2012 was performed for potential candidate genes / genetic polymorphisms relating to cancer cachexia. All candidate genes were reviewed for functional polymorphisms or clinically significant polymorphisms associated with cachexia using the OMIM and GeneRIF databases. Pathway analysis software was used to reveal possible network associations between genes. Functionality of SNPs/genes was explored based on published literature, algorithms for detecting putative deleterious SNPs and interrogating the database for expression of quantitative trait loci (eQTLs). A total of 154 genes associated with cancer cachexia were identified and explored for functional polymorphisms. Of these 154 genes, 119 had a combined total of 281 polymorphisms with functional and/or clinical significance in terms of cachexia associated with them. Of these, 80 polymorphisms (in 51 genes) were replicated in more than one study with 24 polymorphisms found to influence two or more hallmarks of cachexia (i.e., inflammation, loss of fat mass and/or lean mass and reduced survival). Selection of candidate genes and polymorphisms is a key element of multigene study design. The present study provides a contemporary basis to select genes and/or polymorphisms for further association studies in cancer cachexia, and to develop their potential as susceptibility biomarkers of cachexia.

A fruit quality gene map of Prunus

PubMed Central

2009-01-01

Background Prunus fruit development, growth, ripening, and senescence includes major biochemical and sensory changes in texture, color, and flavor. The genetic dissection of these complex processes has important applications in crop improvement, to facilitate maximizing and maintaining stone fruit quality from production and processing through to marketing and consumption. Here we present an integrated fruit quality gene map of Prunus containing 133 genes putatively involved in the determination of fruit texture, pigmentation, flavor, and chilling injury resistance. Results A genetic linkage map of 211 markers was constructed for an intraspecific peach (Prunus persica) progeny population, Pop-DG, derived from a canning peach cultivar 'Dr. Davis' and a fresh market cultivar 'Georgia Belle'. The Pop-DG map covered 818 cM of the peach genome and included three morphological markers, 11 ripening candidate genes, 13 cold-responsive genes, 21 novel EST-SSRs from the ChillPeach database, 58 previously reported SSRs, 40 RAFs, 23 SRAPs, 14 IMAs, and 28 accessory markers from candidate gene amplification. The Pop-DG map was co-linear with the Prunus reference T × E map, with 39 SSR markers in common to align the maps. A further 158 markers were bin-mapped to the reference map: 59 ripening candidate genes, 50 cold-responsive genes, and 50 novel EST-SSRs from ChillPeach, with deduced locations in Pop-DG via comparative mapping. Several candidate genes and EST-SSRs co-located with previously reported major trait loci and quantitative trait loci for chilling injury symptoms in Pop-DG. Conclusion The candidate gene approach combined with bin-mapping and availability of a community-recognized reference genetic map provides an efficient means of locating genes of interest in a target genome. We highlight the co-localization of fruit quality candidate genes with previously reported fruit quality QTLs. The fruit quality gene map developed here is a valuable tool for dissecting the genetic architecture of fruit quality traits in Prunus crops. PMID:19995417

Candidate Gene Identification of Feed Efficiency and Coat Color Traits in a C57BL/6J × Kunming F2 Mice Population Using Genome-Wide Association Study.

PubMed

Miao, Yuanxin; Soudy, Fathia; Xu, Zhong; Liao, Mingxing; Zhao, Shuhong; Li, Xinyun

2017-01-01

Feed efficiency (FE) is a very important trait in livestock industry. Identification of the candidate genes could be of benefit for the improvement of FE trait. Mouse is used as the model for many studies in mammals. In this study, the candidate genes related to FE and coat color were identified using C57BL/6J (C57) × Kunming (KM) F2 mouse population. GWAS results showed that 61 and 2 SNPs were genome-wise suggestive significantly associated with feed conversion ratio (FCR) and feed intake (FI) traits, respectively. Moreover, the Erbin, Msrb2, Ptf1a, and Fgf10 were considered as the candidate genes of FE. The Lpl was considered as the candidate gene of FI. Further, the coat color trait was studied. KM mice are white and C57 ones are black. The GWAS results showed that the most significant SNP was located at chromosome 7, and the closely linked gene was Tyr. Therefore, our study offered useful target genes related to FE in mice; these genes may play similar roles in FE of livestock. Also, we identified the major gene of coat color in mice, which would be useful for better understanding of natural mutation of the coat color in mice.

Expression stability and selection of optimal reference genes for gene expression normalization in early life stage rainbow trout exposed to cadmium and copper.

PubMed

Shekh, Kamran; Tang, Song; Niyogi, Som; Hecker, Markus

2017-09-01

Gene expression analysis represents a powerful approach to characterize the specific mechanisms by which contaminants interact with organisms. One of the key considerations when conducting gene expression analyses using quantitative real-time reverse transcription-polymerase chain reaction (qPCR) is the selection of appropriate reference genes, which is often overlooked. Specifically, to reach meaningful conclusions when using relative quantification approaches, expression levels of reference genes must be highly stable and cannot vary as a function of experimental conditions. However, to date, information on the stability of commonly used reference genes across developmental stages, tissues and after exposure to contaminants such as metals is lacking for many vertebrate species including teleost fish. Therefore, in this study, we assessed the stability of expression of 8 reference gene candidates in the gills and skin of three different early life-stages of rainbow trout after acute exposure (24h) to two metals, cadmium (Cd) and copper (Cu) using qPCR. Candidate housekeeping genes were: beta actin (b-actin), DNA directed RNA polymerase II subunit I (DRP2), elongation factor-1 alpha (EF1a), glyceraldehyde 3-phosphate dehydrogenase (GAPDH), glucose-6-phosphate dehydrogenase (G6PD), hypoxanthine phosphoribosyltransferase (HPRT), ribosomal protein L8 (RPL8), and 18S ribosomal RNA (18S). Four algorithms, geNorm, NormFinder, BestKeeper, and the comparative ΔCt method were employed to systematically evaluate the expression stability of these candidate genes under control and exposed conditions as well as across three different life-stages. Finally, stability of genes was ranked by taking geometric means of the ranks established by the different methods. Stability of reference genes was ranked in the following order (from lower to higher stability): HPRT

Defining the role of the MADS-box gene, Zea agamous like1, in maize domestication

USDA-ARS?s Scientific Manuscript database

Genomic scans for genes that show the signature of past selection have been widely applied to a number of species and have identified a large number of selection candidate genes. In cultivated maize (Zea mays ssp. mays) selection scans have identified several hundred candidate domestication genes...

Genetic and Proteomic Interrogation of Lower Confidence Candidate Genes Reveals Signaling Networks in beta-Catenin-Active Cancers | Office of Cancer Genomics

Cancer.gov

Genome-scale expression studies and comprehensive loss-of-function genetic screens have focused almost exclusively on the highest confidence candidate genes. Here, we describe a strategy for characterizing the lower confidence candidates identified by such approaches.

Genome-wide scan for selection signatures in six cattle breeds in South Africa.

PubMed

Makina, Sithembile O; Muchadeyi, Farai C; van Marle-Köster, Este; Taylor, Jerry F; Makgahlela, Mahlako L; Maiwashe, Azwihangwisi

2015-11-26

The detection of selection signatures in breeds of livestock species can contribute to the identification of regions of the genome that are, or have been, functionally important and, as a consequence, have been targeted by selection. This study used two approaches to detect signatures of selection within and between six cattle breeds in South Africa, including Afrikaner (n = 44), Nguni (n = 54), Drakensberger (n = 47), Bonsmara (n = 44), Angus (n = 31) and Holstein (n = 29). The first approach was based on the detection of genomic regions in which haplotypes have been driven towards complete fixation within breeds. The second approach identified regions of the genome that had very different allele frequencies between populations (F ST). Forty-seven candidate genomic regions were identified as harbouring putative signatures of selection using both methods. Twelve of these candidate selected regions were shared among the breeds and ten were validated by previous studies. Thirty-three of these regions were successfully annotated and candidate genes were identified. Among these genes the keratin genes (KRT222, KRT24, KRT25, KRT26, and KRT27) and one heat shock protein gene (HSPB9) on chromosome 19 between 42,896,570 and 42,897,840 bp were detected for the Nguni breed. These genes were previously associated with adaptation to tropical environments in Zebu cattle. In addition, a number of candidate genes associated with the nervous system (WNT5B, FMOD, PRELP, and ATP2B), immune response (CYM, CDC6, and CDK10), production (MTPN, IGFBP4, TGFB1, and AJAP1) and reproductive performance (ADIPOR2, OVOS2, and RBBP8) were also detected as being under selection. The results presented here provide a foundation for detecting mutations that underlie genetic variation of traits that have economic importance for cattle breeds in South Africa.

Genome-wide association study identifies Loci and candidate genes for body composition and meat quality traits in Beijing-You chickens.

PubMed

Liu, Ranran; Sun, Yanfa; Zhao, Guiping; Wang, Fangjie; Wu, Dan; Zheng, Maiqing; Chen, Jilan; Zhang, Lei; Hu, Yaodong; Wen, Jie

2013-01-01

Body composition and meat quality traits are important economic traits of chickens. The development of high-throughput genotyping platforms and relevant statistical methods have enabled genome-wide association studies in chickens. In order to identify molecular markers and candidate genes associated with body composition and meat quality traits, genome-wide association studies were conducted using the Illumina 60 K SNP Beadchip to genotype 724 Beijing-You chickens. For each bird, a total of 16 traits were measured, including carcass weight (CW), eviscerated weight (EW), dressing percentage, breast muscle weight (BrW) and percentage (BrP), thigh muscle weight and percentage, abdominal fat weight and percentage, dry matter and intramuscular fat contents of breast and thigh muscle, ultimate pH, and shear force of the pectoralis major muscle at 100 d of age. The SNPs that were significantly associated with the phenotypic traits were identified using both simple (GLM) and compressed mixed linear (MLM) models. For nine of ten body composition traits studied, SNPs showing genome wide significance (P<2.59E-6) have been identified. A consistent region on chicken (Gallus gallus) chromosome 4 (GGA4), including seven significant SNPs and four candidate genes (LCORL, LAP3, LDB2, TAPT1), were found to be associated with CW and EW. Another 0.65 Mb region on GGA3 for BrW and BrP was identified. After measuring the mRNA content in beast muscle for five genes located in this region, the changes in GJA1 expression were found to be consistent with that of breast muscle weight across development. It is highly possible that GJA1 is a functional gene for breast muscle development in chickens. For meat quality traits, several SNPs reaching suggestive association were identified and possible candidate genes with their functions were discussed.

A Controlled Pharmacogenetic Trial of Sibutramine on Weight Loss and Body Composition in Obese or Overweight Adults

PubMed Central

Grudell, April B.M.; Sweetser, Seth; Camilleri, Michael; Eckert, Deborah J.; Vazquez-Roque, Maria I.; Carlson, Paula J.; Burton, Duane D.; Braddock, Autumn E.; Clark, Matthew M.; Graszer, Karen M.; Kalsy, Sarah A.; Zinsmeister, Alan R.

2008-01-01

Background/ Aim Weight loss in response to sibutramine is highly variable. We assessed the association of specific markers of polymorphisms of candidate a2A adrenoreceptor, 5-HT transporter and GNβ3 genes and weight loss with sibutramine. Methods We conducted a randomized, double-blind, pharmacogenetic study of behavioral therapy and sibutramine (10 or 15 mg daily) or placebo for 12 weeks in 181 overweight or obese participants. We measured body weight, BMI, body composition, gastric emptying and genetic variation (α2A C1291G, 5-HTTLPR, and GNβ3 C825T genotypes). ANCOVA was used to assess treatment effects on, and associations of the specific markers of candidate genes with weight loss and body composition. Results Sibutramine, 10 and 15 mg, caused significant weight loss (p = 0.009); there was a statistically significant gene by dose interaction for GNβ3 genotype. For each candidate gene, significant treatment effects at 12 weeks were observed (p<0.017) for all specific genotype variants (delta weight loss in the 2 sibutramine doses versus placebo): α2A CC genotype ( Δ ~5kg), GNβ3 TC/TT genotype (Δ ~6kg), and 5-HTTLPR LS/SS (Δ ~4.5kg). Gene pairs resulted in significantly greater sibutramine treatment effects on weight (both p<0.002): in participants with 5-HTTLPR LS/SS with GNβ3 TC/TT, Δ ~6kg and those with a2A CC with GNβ3 TC/TT, Δ ~8kg; however, effects were not synergistic. Treatment with sibutramine also resulted in significantly greater reduction of body fat for specific α2A CC and GNβ3 TC/TT genotype variants individually (both p<0.02). Conclusions Selection of patients with obesity based on candidate genes may enhance response to multidimensional sibutramine and behavioral therapy. PMID:18725220

Combined serial analysis of gene expression and transcription factor binding site prediction identifies novel-candidate-target genes of Nr2e1 in neocortex development.

PubMed

Schmouth, Jean-François; Arenillas, David; Corso-Díaz, Ximena; Xie, Yuan-Yun; Bohacec, Slavita; Banks, Kathleen G; Bonaguro, Russell J; Wong, Siaw H; Jones, Steven J M; Marra, Marco A; Simpson, Elizabeth M; Wasserman, Wyeth W

2015-07-24

Nr2e1 (nuclear receptor subfamily 2, group e, member 1) encodes a transcription factor important in neocortex development. Previous work has shown that nuclear receptors can have hundreds of target genes, and bind more than 300 co-interacting proteins. However, recognition of the critical role of Nr2e1 in neural stem cells and neocortex development is relatively recent, thus the molecular mechanisms involved for this nuclear receptor are only beginning to be understood. Serial analysis of gene expression (SAGE), has given researchers both qualitative and quantitative information pertaining to biological processes. Thus, in this work, six LongSAGE mouse libraries were generated from laser microdissected tissue samples of dorsal VZ/SVZ (ventricular zone and subventricular zone) from the telencephalon of wild-type (Wt) and Nr2e1-null embryos at the critical development ages E13.5, E15.5, and E17.5. We then used a novel approach, implementing multiple computational methods followed by biological validation to further our understanding of Nr2e1 in neocortex development. In this work, we have generated a list of 1279 genes that are differentially expressed in response to altered Nr2e1 expression during in vivo neocortex development. We have refined this list to 64 candidate direct-targets of NR2E1. Our data suggested distinct roles for Nr2e1 during different neocortex developmental stages. Most importantly, our results suggest a possible novel pathway by which Nr2e1 regulates neurogenesis, which includes Lhx2 as one of the candidate direct-target genes, and SOX9 as a co-interactor. In conclusion, we have provided new candidate interacting partners and numerous well-developed testable hypotheses for understanding the pathways by which Nr2e1 functions to regulate neocortex development.

A candidate gene study in low HDL-cholesterol families provides evidence for the involvement of the APOA2 gene and the APOA1C3A4 gene cluster.

PubMed

Lilja, Heidi E; Soro, Aino; Ylitalo, Kati; Nuotio, Ilpo; Viikari, Jorma S A; Salomaa, Veikko; Vartiainen, Erkki; Taskinen, Marja-Riitta; Peltonen, Leena; Pajukanta, Päivi

2002-09-01

In patients with premature coronary heart disease, the most common lipoprotein abnormality is high-density lipoprotein (HDL) deficiency. To assess the genetic background of the low HDL-cholesterol trait, we performed a candidate gene study in 25 families with low HDL, collected from the genetically isolated population of Finland. We studied 21 genes encoding essential proteins involved in the HDL metabolism by genotyping intragenic and flanking markers for these genes. We found suggestive evidence for linkage in two candidate regions: Marker D1S2844, in the apolipoprotein A-II (APOA2) region, yielded a LOD score of 2.14 and marker D11S939 flanking the apolipoprotein A-I/C-III/A-IV gene cluster (APOA1C3A4) produced a LOD score of 1.69. Interestingly, we identified potential shared haplotypes in these two regions in a subset of low HDL families. These families also contributed to the obtained positive LOD scores, whereas the rest of the families produced negative LOD scores. None of the remaining candidate regions provided any evidence for linkage. Since only a limited number of loci were tested in this candidate gene study, these LOD scores suggest significant involvement of the APOA2 gene and the APOA1C3A4 gene cluster, or loci in their immediate vicinity, in the pathogenesis of low HDL.

Combining mouse mammary gland gene expression and comparative mapping for the identification of candidate genes for QTL of milk production traits in cattle

PubMed Central

Ron, Micha; Israeli, Galit; Seroussi, Eyal; Weller, Joel I; Gregg, Jeffrey P; Shani, Moshe; Medrano, Juan F

2007-01-01

Background Many studies have found segregating quantitative trait loci (QTL) for milk production traits in different dairy cattle populations. However, even for relatively large effects with a saturated marker map the confidence interval for QTL location by linkage analysis spans tens of map units, or hundreds of genes. Combining mapping and arraying has been suggested as an approach to identify candidate genes. Thus, gene expression analysis in the mammary gland of genes positioned in the confidence interval of the QTL can bridge the gap between fine mapping and quantitative trait nucleotide (QTN) determination. Results We hybridized Affymetrix microarray (MG-U74v2), containing 12,488 murine probes, with RNA derived from mammary gland of virgin, pregnant, lactating and involuting C57BL/6J mice in a total of nine biological replicates. We combined microarray data from two additional studies that used the same design in mice with a total of 75 biological replicates. The same filtering and normalization was applied to each microarray data using GeneSpring software. Analysis of variance identified 249 differentially expressed probe sets common to the three experiments along the four developmental stages of puberty, pregnancy, lactation and involution. 212 genes were assigned to their bovine map positions through comparative mapping, and thus form a list of candidate genes for previously identified QTLs for milk production traits. A total of 82 of the genes showed mammary gland-specific expression with at least 3-fold expression over the median representing all tissues tested in GeneAtlas. Conclusion This work presents a web tool for candidate genes for QTL (cgQTL) that allows navigation between the map of bovine milk production QTL, potential candidate genes and their level of expression in mammary gland arrays and in GeneAtlas. Three out of four confirmed genes that affect QTL in livestock (ABCG2, DGAT1, GDF8, IGF2) were over expressed in the target organ. Thus, cgQTL can be used to determine priority of candidate genes for QTN analysis based on differential expression in the target organ. PMID:17584498

Molecular genetics and animal models in autistic disorder.

PubMed

Andres, Christian

2002-01-01

Autistic disorder is a behavioural syndrome beginning before the age of 3 years and lasting over the whole lifetime. It is characterised by impaired communication, impaired social interactions, and repetitive interests and behaviour. The prevalence is about 7/10,000 taking a restrictive definition and more than 1/500 with a broader definition, including all the pervasive developmental disorders. The importance of genetic factors has been highlighted by epidemiological studies showing that autistic disorder is one of the most genetic neuropsychiatric diseases. The relative risk of first relatives is about 100-fold higher than the risk in the normal population and the concordance in monozygotic twin is about 60%. Different strategies have been applied on the track of susceptibility genes. The systematic search of linked loci led to contradictory results, in part due to the heterogeneity of the clinical definitions, to the differences in the DNA markers, and to the different methods of analysis used. An oversimplification of the inferred model is probably also cause of our disappointment. More work is necessary to give a clearer picture. One region emerges more frequently: the long arm of chromosome 7. Several candidate genes have been studied and some gave indications of association: the Reelin gene and the Wnt2 gene. Cytogenetical abnormalities are frequent at 15q11-13, the region of the Angelman and Prader-Willi syndrome. Imprinting plays an important role in this region, no candidate gene has been identified in autism. Biochemical abnormalities have been found in the serotonin system. Association and linkage studies gave no consistent results with some serotonin receptors and in the transporter, although it seems interesting to go further in the biochemical characterisation of the serotonin transporter activity, particularly in platelets, easily accessible. Two monogenic diseases have been associated with autistic disorder: tuberous sclerosis and fragile X. A better knowledge of the pathophysiology of these disorders can help to understand autism. Different other candidate genes have been tested, positive results await replications in other samples. Animal models have been developed, generally by knocking out the different candidate genes. Behaviour studies have mainly focused on anxiety and learning paradigms. Another group of models results from surgical or toxic lesions of candidate regions in the brain, in general during development. The tools to analyse these animals are not yet standardised, and an important effort needs to be undertaken.

Identification of immunohistochemical markers for distinguishing lung adenocarcinoma from squamous cell carcinoma

PubMed Central

Zhan, Cheng; Yan, Li; Wang, Lin; Sun, Yang; Wang, Xingxing; Lin, Zongwu; Zhang, Yongxing; Wang, Qun

2015-01-01

Background Immunohistochemical staining has been widely used in distinguishing lung adenocarcinoma (LUAD) from lung squamous cell carcinoma (LUSC), which is of vital importance for the diagnosis and treatment of lung cancer. Due to the lack of a comprehensive analysis of different lung cancer subtypes, there may still be undiscovered markers with higher diagnostic accuracy. Methods Herein first, we systematically analyzed high-throughput data obtained from The Cancer Genome Atlas (TCGA) database. Combining differently expressed gene screening and receiver operating characteristic (ROC) curve analysis, we attempted to identify the genes which might be suitable as immunohistochemical markers in distinguishing LUAD from LUSC. Then we detected the expression of six of these genes (MLPH, TMC5, SFTA3, DSG3, DSC3 and CALML3) in lung cancer sections using immunohistochemical staining. Results A number of genes were identified as candidate immunohistochemical markers with high sensitivity and specificity in distinguishing LUAD from LUSC. Then the staining results confirmed the potentials of the six genes (MLPH, TMC5, SFTA3, DSG3, DSC3 and CALML3) in distinguishing LUAD from LUSC, and their sensitivity and specificity were not less than many commonly used markers. Conclusions The results revealed that the six genes (MLPH, TMC5, SFTA3, DSG3, DSC3 and CALML3) might be suitable markers in distinguishing LUAD from LUSC, and also validated the feasibility of our methods for identification of candidate markers from high-throughput data. PMID:26380766

Meta-analysis of heterogeneous data sources for genome-scale identification of risk genes in complex phenotypes.

PubMed

Pers, Tune H; Hansen, Niclas Tue; Lage, Kasper; Koefoed, Pernille; Dworzynski, Piotr; Miller, Martin Lee; Flint, Tracey J; Mellerup, Erling; Dam, Henrik; Andreassen, Ole A; Djurovic, Srdjan; Melle, Ingrid; Børglum, Anders D; Werge, Thomas; Purcell, Shaun; Ferreira, Manuel A; Kouskoumvekaki, Irene; Workman, Christopher T; Hansen, Torben; Mors, Ole; Brunak, Søren

2011-07-01

Meta-analyses of large-scale association studies typically proceed solely within one data type and do not exploit the potential complementarities in other sources of molecular evidence. Here, we present an approach to combine heterogeneous data from genome-wide association (GWA) studies, protein-protein interaction screens, disease similarity, linkage studies, and gene expression experiments into a multi-layered evidence network which is used to prioritize the entire protein-coding part of the genome identifying a shortlist of candidate genes. We report specifically results on bipolar disorder, a genetically complex disease where GWA studies have only been moderately successful. We validate one such candidate experimentally, YWHAH, by genotyping five variations in 640 patients and 1,377 controls. We found a significant allelic association for the rs1049583 polymorphism in YWHAH (adjusted P = 5.6e-3) with an odds ratio of 1.28 [1.12-1.48], which replicates a previous case-control study. In addition, we demonstrate our approach's general applicability by use of type 2 diabetes data sets. The method presented augments moderately powered GWA data, and represents a validated, flexible, and publicly available framework for identifying risk genes in highly polygenic diseases. The method is made available as a web service at www.cbs.dtu.dk/services/metaranker. © 2011 Wiley-Liss, Inc.

Association of candidate gene polymorphisms with clinical subtypes of preterm birth in a Latin American population

PubMed Central

Gimenez, Lucas G.; Momany, Allison M.; Poletta, Fernando A.; Krupitzki, Hugo B.; Gili, Juan A.; Busch, Tamara D.; Saleme, Cesar; Cosentino, Viviana R.; Pawluk, Mariela S.; Campaña, Hebe; Gadow, Enrique C.; Murray, Jeffrey C.; Lopez-Camelo, Jorge S.

2017-01-01

Background Preterm birth (PTB) is the leading cause of neonatal mortality and morbidity. PTB is often classified according to clinical presentation: Idiopathic (PTB-I), preterm premature rupture of membranes (PTB-PPROM), and medically induced (PTB-M). The aim of this study was to evaluate the associations between specific candidate genes and clinical subtypes of PTB. Methods 24 SNPs were genotyped in 18 candidate genes in 709 infant triads. Of them, 243 were PTB-I, 256 PTB-PPROM, and 210 PTB-M. These data were analyzed with a Family-Based Association. Results PTB was nominally associated with rs2272365 in PON1, rs883319 in KCNN3, rs4458044 in CRHR1, and rs610277 in F3. Regarding clinical subtypes analysis, 3 SNPs were associated with PTB-I (rs2272365 in PON1, rs10178458 in COL4A3, and rs4458044 in CRHR1), rs610277 in F3 was associated with PTB-PPROM, and rs883319 in KCNN3 and rs610277 in F3 were associated with PTB-M. Conclusions Our study identified polymorphisms potentially associated with specific clinical subtypes of PTB in this Latin American population. These results could suggest a specific role of such genes in the mechanisms involved in each clinical subtype. Further studies are required to confirm our results and to determine the role of these genes in the pathophysiology of clinical subtypes. PMID:28426651

Association of candidate gene polymorphisms with clinical subtypes of preterm birth in a Latin American population.

PubMed

Gimenez, Lucas G; Momany, Allison M; Poletta, Fernando A; Krupitzki, Hugo B; Gili, Juan A; Busch, Tamara D; Saleme, Cesar; Cosentino, Viviana R; Pawluk, Mariela S; Campaña, Hebe; Gadow, Enrique C; Murray, Jeffrey C; Lopez-Camelo, Jorge S

2017-09-01

BackgroundPreterm birth (PTB) is the leading cause of neonatal mortality and morbidity. PTB is often classified according to clinical presentation as follows: idiopathic (PTB-I), preterm premature rupture of membranes (PTB-PPROM), and medically induced (PTB-M). The aim of this study was to evaluate the associations between specific candidate genes and clinical subtypes of PTB.MethodsTwenty-four single-nucleotide polymorphisms (SNPs) were genotyped in 18 candidate genes in 709 infant triads. Of them, 243 were PTB-I, 256 were PTB-PPROM, and 210 were PTB-M. These data were analyzed with a Family-Based Association.ResultsPTB was nominally associated with rs2272365 in PON1, rs883319 in KCNN3, rs4458044 in CRHR1, and rs610277 in F3. Regarding clinical subtypes analysis, three SNPs were associated with PTB-I (rs2272365 in PON1, rs10178458 in COL4A3, and rs4458044 in CRHR1), rs610277 in F3 was associated with PTB-PPROM, and rs883319 in KCNN3 and rs610277 in F3 were associated with PTB-M.ConclusionOur study identified polymorphisms potentially associated with specific clinical subtypes of PTB in this Latin American population. These results could suggest a specific role of such genes in the mechanisms involved in each clinical subtype. Further studies are required to confirm our results and to determine the role of these genes in the pathophysiology of clinical subtypes.

RNA-Seq identification of candidate defense genes targeted by endophytic Bacillus cereus-mediated induced systemic resistance against Meloidogyne incognita in tomato.

PubMed

Hu, Haijing; Wang, Cong; Li, Xia; Tang, Yunyun; Wang, Yufang; Chen, Shuanglin; Yan, Shuzhen

2018-05-08

The endophytic bacteria Bacillus cereus BCM2 has shown great potential as a defense against the parasitic nematode Meloidogyne incognita. Here, we studied the endophytic bacteria-mediated plant defense against M. incognita and searched for defense-related candidate genes using RNA-Seq. The induced systemic resistance of BCM2 against M. incognita was tested using the split-root method. Pre-inoculated BCM2 on the inducer side was associated with a dramatic reduction in galls and egg masses at the responder side, but inoculated BCM2 alone did not produce the same effect. In order to investigate which plant defense-related genes are specifically activated by BCM2, four RNA samples from tomato roots were sequenced, and four high quality total clean bases were obtained, ranging from 6.64 to 6.75 Gb, with an average of 21558 total genes. The 34 candidate defense-related genes were identified by pair-wise comparison among libraries, representing the targets for BCM2 priming resistance against M. incognita. Functional characterization revealed that the plant-pathogen interaction pathway (ID: ko04626) was significantly enriched for BCM2-mediated M. incognita resistance. This study demonstrates that B. cereus BCM2 maintains a harmonious host-microbe relationship with tomato, but appeared to prime the plant, resulting in more vigorous defense response toward the infection nematode. This article is protected by copyright. All rights reserved.

HGPEC: a Cytoscape app for prediction of novel disease-gene and disease-disease associations and evidence collection based on a random walk on heterogeneous network.

PubMed

Le, Duc-Hau; Pham, Van-Huy

2017-06-15

Finding gene-disease and disease-disease associations play important roles in the biomedical area and many prioritization methods have been proposed for this goal. Among them, approaches based on a heterogeneous network of genes and diseases are considered state-of-the-art ones, which achieve high prediction performance and can be used for diseases with/without known molecular basis. Here, we developed a Cytoscape app, namely HGPEC, based on a random walk with restart algorithm on a heterogeneous network of genes and diseases. This app can prioritize candidate genes and diseases by employing a heterogeneous network consisting of a network of genes/proteins and a phenotypic disease similarity network. Based on the rankings, novel disease-gene and disease-disease associations can be identified. These associations can be supported with network- and rank-based visualization as well as evidences and annotations from biomedical data. A case study on prediction of novel breast cancer-associated genes and diseases shows the abilities of HGPEC. In addition, we showed prominence in the performance of HGPEC compared to other tools for prioritization of candidate disease genes. Taken together, our app is expected to effectively predict novel disease-gene and disease-disease associations and support network- and rank-based visualization as well as biomedical evidences for such the associations.

QTL Analysis of Dietary Obesity in C57BL/6byj X 129P3/J F2 Mice: Diet- and Sex-Dependent Effects

PubMed Central

Lin, Cailu; Theodorides, Maria L.; McDaniel, Amanda H.; Tordoff, Michael G.; Zhang, Qinmin; Li, Xia; Bosak, Natalia; Bachmanov, Alexander A.; Reed, Danielle R.

2013-01-01

Obesity is a heritable trait caused by complex interactions between genes and environment, including diet. Gene-by-diet interactions are difficult to study in humans because the human diet is hard to control. Here, we used mice to study dietary obesity genes, by four methods. First, we bred 213 F2 mice from strains that are susceptible [C57BL/6ByJ (B6)] or resistant [129P3/J (129)] to dietary obesity. Percent body fat was assessed after mice ate low-energy diet and again after the same mice ate high-energy diet for 8 weeks. Linkage analyses identified QTLs associated with dietary obesity. Three methods were used to filter candidate genes within the QTL regions: (a) association mapping was conducted using >40 strains; (b) differential gene expression and (c) comparison of genomic DNA sequence, using two strains closely related to the progenitor strains from Experiment 1. The QTL effects depended on whether the mice were male or female or which diet they were recently fed. After feeding a low-energy diet, percent body fat was linked to chr 7 (LOD = 3.42). After feeding a high-energy diet, percent body fat was linked to chr 9 (Obq5; LOD = 3.88), chr 12 (Obq34; LOD = 3.88), and chr 17 (LOD = 4.56). The Chr 7 and 12 QTLs were sex dependent and all QTL were diet-dependent. The combination of filtering methods highlighted seven candidate genes within the QTL locus boundaries: Crx, Dmpk, Ahr, Mrpl28, Glo1, Tubb5, and Mut. However, these filtering methods have limitations so gene identification will require alternative strategies, such as the construction of congenics with very small donor regions. PMID:23922663

Breast Tumors with Elevated Expression of 1q Candidate Genes Confer Poor Clinical Outcome and Sensitivity to Ras/PI3K Inhibition

PubMed Central

Viveka Thangaraj, Soundara; Periasamy, Jayaprakash; Bhaskar Rao, Divya; Barnabas, Georgina D.; Raghavan, Swetha; Ganesan, Kumaresan

2013-01-01

Genomic aberrations are common in cancers and the long arm of chromosome 1 is known for its frequent amplifications in breast cancer. However, the key candidate genes of 1q, and their contribution in breast cancer pathogenesis remain unexplored. We have analyzed the gene expression profiles of 1635 breast tumor samples using meta-analysis based approach and identified clinically significant candidates from chromosome 1q. Seven candidate genes including exonuclease 1 (EXO1) are consistently over expressed in breast tumors, specifically in high grade and aggressive breast tumors with poor clinical outcome. We derived a EXO1 co-expression module from the mRNA profiles of breast tumors which comprises 1q candidate genes and their co-expressed genes. By integrative functional genomics investigation, we identified the involvement of EGFR, RAS, PI3K / AKT, MYC, E2F signaling in the regulation of these selected 1q genes in breast tumors and breast cancer cell lines. Expression of EXO1 module was found as indicative of elevated cell proliferation, genomic instability, activated RAS/AKT/MYC/E2F1 signaling pathways and loss of p53 activity in breast tumors. mRNA–drug connectivity analysis indicates inhibition of RAS/PI3K as a possible targeted therapeutic approach for the patients with activated EXO1 module in breast tumors. Thus, we identified seven 1q candidate genes strongly associated with the poor survival of breast cancer patients and identified the possibility of targeting them with EGFR/RAS/PI3K inhibitors. PMID:24147022

Exome-wide DNA capture and next generation sequencing in domestic and wild species.

PubMed

Cosart, Ted; Beja-Pereira, Albano; Chen, Shanyuan; Ng, Sarah B; Shendure, Jay; Luikart, Gordon

2011-07-05

Gene-targeted and genome-wide markers are crucial to advance evolutionary biology, agriculture, and biodiversity conservation by improving our understanding of genetic processes underlying adaptation and speciation. Unfortunately, for eukaryotic species with large genomes it remains costly to obtain genome sequences and to develop genome resources such as genome-wide SNPs. A method is needed to allow gene-targeted, next-generation sequencing that is flexible enough to include any gene or number of genes, unlike transcriptome sequencing. Such a method would allow sequencing of many individuals, avoiding ascertainment bias in subsequent population genetic analyses.We demonstrate the usefulness of a recent technology, exon capture, for genome-wide, gene-targeted marker discovery in species with no genome resources. We use coding gene sequences from the domestic cow genome sequence (Bos taurus) to capture (enrich for), and subsequently sequence, thousands of exons of B. taurus, B. indicus, and Bison bison (wild bison). Our capture array has probes for 16,131 exons in 2,570 genes, including 203 candidate genes with known function and of interest for their association with disease and other fitness traits. We successfully sequenced and mapped exon sequences from across the 29 autosomes and X chromosome in the B. taurus genome sequence. Exon capture and high-throughput sequencing identified thousands of putative SNPs spread evenly across all reference chromosomes, in all three individuals, including hundreds of SNPs in our targeted candidate genes. This study shows exon capture can be customized for SNP discovery in many individuals and for non-model species without genomic resources. Our captured exome subset was small enough for affordable next-generation sequencing, and successfully captured exons from a divergent wild species using the domestic cow genome as reference.

Development of RNAi method for screening candidate genes to control emerald ash borer, Agrilus planipennis

USDA-ARS?s Scientific Manuscript database

Emerald ash borer (EAB), a serious invasive forest pest in the United States, has killed millions of North American ash trees and spread to 29 states since it was first detected in 2002 in southern Michigan. Development of a new control method that specifically targets the pest but has no adverse i...

Mapping a candidate gene (MdMYB10) for red flesh and foliage colour in apple

PubMed Central

Chagné, David; Carlisle, Charmaine M; Blond, Céline; Volz, Richard K; Whitworth, Claire J; Oraguzie, Nnadozie C; Crowhurst, Ross N; Allan, Andrew C; Espley, Richard V; Hellens, Roger P; Gardiner, Susan E

2007-01-01

Background Integrating plant genomics and classical breeding is a challenge for both plant breeders and molecular biologists. Marker-assisted selection (MAS) is a tool that can be used to accelerate the development of novel apple varieties such as cultivars that have fruit with anthocyanin through to the core. In addition, determining the inheritance of novel alleles, such as the one responsible for red flesh, adds to our understanding of allelic variation. Our goal was to map candidate anthocyanin biosynthetic and regulatory genes in a population segregating for the red flesh phenotypes. Results We have identified the Rni locus, a major genetic determinant of the red foliage and red colour in the core of apple fruit. In a population segregating for the red flesh and foliage phenotype we have determined the inheritance of the Rni locus and DNA polymorphisms of candidate anthocyanin biosynthetic and regulatory genes. Simple Sequence Repeats (SSRs) and Single Nucleotide Polymorphisms (SNPs) in the candidate genes were also located on an apple genetic map. We have shown that the MdMYB10 gene co-segregates with the Rni locus and is on Linkage Group (LG) 09 of the apple genome. Conclusion We have performed candidate gene mapping in a fruit tree crop and have provided genetic evidence that red colouration in the fruit core as well as red foliage are both controlled by a single locus named Rni. We have shown that the transcription factor MdMYB10 may be the gene underlying Rni as there were no recombinants between the marker for this gene and the red phenotype in a population of 516 individuals. Associating markers derived from candidate genes with a desirable phenotypic trait has demonstrated the application of genomic tools in a breeding programme of a horticultural crop species. PMID:17608951

Antennal transcriptome analysis of the piercing moth Oraesia emarginata (Lepidoptera: Noctuidae)

PubMed Central

Feng, Bo; Guo, Qianshuang; Zheng, Kaidi; Qin, Yuanxia; Du, Yongjun

2017-01-01

The piercing fruit moth Oraesia emarginata is an economically significant pest; however, our understanding of its olfactory mechanisms in infestation is limited. The present study conducted antennal transcriptome analysis of olfactory genes using real-time quantitative reverse transcription PCR analysis (RT-qPCR). We identified a total of 104 candidate chemosensory genes from several gene families, including 35 olfactory receptors (ORs), 41 odorant-binding proteins, 20 chemosensory proteins, 6 ionotropic receptors, and 2 sensory neuron membrane proteins. Seven candidate pheromone receptors (PRs) and 3 candidate pheromone-binding proteins (PBPs) for sex pheromone recognition were found. OemaOR29 and OemaPBP1 had the highest fragments per kb per million fragments (FPKM) values in all ORs and OBPs, respectively. Eighteen olfactory genes were upregulated in females, including 5 candidate PRs, and 20 olfactory genes were upregulated in males, including 2 candidate PRs (OemaOR29 and 4) and 2 PBPs (OemaPBP1 and 3). These genes may have roles in mediating sex-specific behaviors. Most candidate olfactory genes of sex pheromone recognition (except OemaOR29 and OemaPBP3) in O. emarginata were not clustered with those of studied noctuid species (type I pheromone). In addition, OemaOR29 was belonged to cluster PRIII, which comprise proteins that recognize type II pheromones instead of type I pheromones. The structure and function of olfactory genes that encode sex pheromones in O. emarginata might thus differ from those of other studied noctuids. The findings of the present study may help explain the molecular mechanism underlying olfaction and the evolution of olfactory genes encoding sex pheromones in O. emarginata. PMID:28614384

Elevated transcription factor specificity protein 1 in autistic brains alters the expression of autism candidate genes.

PubMed

Thanseem, Ismail; Anitha, Ayyappan; Nakamura, Kazuhiko; Suda, Shiro; Iwata, Keiko; Matsuzaki, Hideo; Ohtsubo, Masafumi; Ueki, Takatoshi; Katayama, Taiichi; Iwata, Yasuhide; Suzuki, Katsuaki; Minoshima, Shinsei; Mori, Norio

2012-03-01

Profound changes in gene expression can result from abnormalities in the concentrations of sequence-specific transcription factors like specificity protein 1 (Sp1). Specificity protein 1 binding sites have been reported in the promoter regions of several genes implicated in autism. We hypothesize that dysfunction of Sp1 could affect the expression of multiple autism candidate genes, contributing to the heterogeneity of autism. We assessed any alterations in the expression of Sp1 and that of autism candidate genes in the postmortem brain (anterior cingulate gyrus [ACG], motor cortex, and thalamus) of autism patients (n = 8) compared with healthy control subjects (n = 13). Alterations in the expression of candidate genes upon Sp1/DNA binding inhibition with mithramycin and Sp1 silencing by RNAi were studied in SK-N-SH neuronal cells. We observed elevated expression of Sp1 in ACG of autism patients (p = .010). We also observed altered expression of several autism candidate genes. GABRB3, RELN, and HTR2A showed reduced expression, whereas CD38, ITGB3, MAOA, MECP2, OXTR, and PTEN showed elevated expression in autism. In SK-N-SH cells, OXTR, PTEN, and RELN showed reduced expression upon Sp1/DNA binding inhibition and Sp1 silencing. The RNA integrity number was not available for any of the samples. Transcription factor Sp1 is dysfunctional in the ACG of autistic brain. Consequently, the expression of potential autism candidate genes regulated by Sp1, especially OXTR and PTEN, could be affected. The diverse downstream pathways mediated by the Sp1-regulated genes, along with the environmental and intracellular signal-related regulation of Sp1, could explain the complex phenotypes associated with autism.

EBF factors drive expression of multiple classes of target genes governing neuronal development.

PubMed

Green, Yangsook S; Vetter, Monica L

2011-04-30

Early B cell factor (EBF) family members are transcription factors known to have important roles in several aspects of vertebrate neurogenesis, including commitment, migration and differentiation. Knowledge of how EBF family members contribute to neurogenesis is limited by a lack of detailed understanding of genes that are transcriptionally regulated by these factors. We performed a microarray screen in Xenopus animal caps to search for targets of EBF transcriptional activity, and identified candidate targets with multiple roles, including transcription factors of several classes. We determined that, among the most upregulated candidate genes with expected neuronal functions, most require EBF activity for some or all of their expression, and most have overlapping expression with ebf genes. We also found that the candidate target genes that had the most strongly overlapping expression patterns with ebf genes were predicted to be direct transcriptional targets of EBF transcriptional activity. The identification of candidate targets that are transcription factor genes, including nscl-1, emx1 and aml1, improves our understanding of how EBF proteins participate in the hierarchy of transcription control during neuronal development, and suggests novel mechanisms by which EBF activity promotes migration and differentiation. Other candidate targets, including pcdh8 and kcnk5, expand our knowledge of the types of terminal differentiated neuronal functions that EBF proteins regulate.

Identification of candidate transmission-blocking antigen genes in Theileria annulata and related vector-borne apicomplexan parasites.

PubMed

Lempereur, Laetitia; Larcombe, Stephen D; Durrani, Zeeshan; Karagenc, Tulin; Bilgic, Huseyin Bilgin; Bakirci, Serkan; Hacilarlioglu, Selin; Kinnaird, Jane; Thompson, Joanne; Weir, William; Shiels, Brian

2017-06-05

Vector-borne apicomplexan parasites are a major cause of mortality and morbidity to humans and livestock globally. The most important disease syndromes caused by these parasites are malaria, babesiosis and theileriosis. Strategies for control often target parasite stages in the mammalian host that cause disease, but this can result in reservoir infections that promote pathogen transmission and generate economic loss. Optimal control strategies should protect against clinical disease, block transmission and be applicable across related genera of parasites. We have used bioinformatics and transcriptomics to screen for transmission-blocking candidate antigens in the tick-borne apicomplexan parasite, Theileria annulata. A number of candidate antigen genes were identified which encoded amino acid domains that are conserved across vector-borne Apicomplexa (Babesia, Plasmodium and Theileria), including the Pfs48/45 6-cys domain and a novel cysteine-rich domain. Expression profiling confirmed that selected candidate genes are expressed by life cycle stages within infected ticks. Additionally, putative B cell epitopes were identified in the T. annulata gene sequences encoding the 6-cys and cysteine rich domains, in a gene encoding a putative papain-family cysteine peptidase, with similarity to the Plasmodium SERA family, and the gene encoding the T. annulata major merozoite/piroplasm surface antigen, Tams1. Candidate genes were identified that encode proteins with similarity to known transmission blocking candidates in related parasites, while one is a novel candidate conserved across vector-borne apicomplexans and has a potential role in the sexual phase of the life cycle. The results indicate that a 'One Health' approach could be utilised to develop a transmission-blocking strategy effective against vector-borne apicomplexan parasites of animals and humans.

The genome sequence of the most widely cultivated cacao type and its use to identify candidate genes regulating pod color.

PubMed

Motamayor, Juan C; Mockaitis, Keithanne; Schmutz, Jeremy; Haiminen, Niina; Livingstone, Donald; Cornejo, Omar; Findley, Seth D; Zheng, Ping; Utro, Filippo; Royaert, Stefan; Saski, Christopher; Jenkins, Jerry; Podicheti, Ram; Zhao, Meixia; Scheffler, Brian E; Stack, Joseph C; Feltus, Frank A; Mustiga, Guiliana M; Amores, Freddy; Phillips, Wilbert; Marelli, Jean Philippe; May, Gregory D; Shapiro, Howard; Ma, Jianxin; Bustamante, Carlos D; Schnell, Raymond J; Main, Dorrie; Gilbert, Don; Parida, Laxmi; Kuhn, David N

2013-06-03

Theobroma cacao L. cultivar Matina 1-6 belongs to the most cultivated cacao type. The availability of its genome sequence and methods for identifying genes responsible for important cacao traits will aid cacao researchers and breeders. We describe the sequencing and assembly of the genome of Theobroma cacao L. cultivar Matina 1-6. The genome of the Matina 1-6 cultivar is 445 Mbp, which is significantly larger than a sequenced Criollo cultivar, and more typical of other cultivars. The chromosome-scale assembly, version 1.1, contains 711 scaffolds covering 346.0 Mbp, with a contig N50 of 84.4 kbp, a scaffold N50 of 34.4 Mbp, and an evidence-based gene set of 29,408 loci. Version 1.1 has 10x the scaffold N50 and 4x the contig N50 as Criollo, and includes 111 Mb more anchored sequence. The version 1.1 assembly has 4.4% gap sequence, while Criollo has 10.9%. Through a combination of haplotype, association mapping and gene expression analyses, we leverage this robust reference genome to identify a promising candidate gene responsible for pod color variation. We demonstrate that green/red pod color in cacao is likely regulated by the R2R3 MYB transcription factor TcMYB113, homologs of which determine pigmentation in Rosaceae, Solanaceae, and Brassicaceae. One SNP within the target site for a highly conserved trans-acting siRNA in dicots, found within TcMYB113, seems to affect transcript levels of this gene and therefore pod color variation. We report a high-quality sequence and annotation of Theobroma cacao L. and demonstrate its utility in identifying candidate genes regulating traits.

Phenome-driven disease genetics prediction toward drug discovery.

PubMed

Chen, Yang; Li, Li; Zhang, Guo-Qiang; Xu, Rong

2015-06-15

Discerning genetic contributions to diseases not only enhances our understanding of disease mechanisms, but also leads to translational opportunities for drug discovery. Recent computational approaches incorporate disease phenotypic similarities to improve the prediction power of disease gene discovery. However, most current studies used only one data source of human disease phenotype. We present an innovative and generic strategy for combining multiple different data sources of human disease phenotype and predicting disease-associated genes from integrated phenotypic and genomic data. To demonstrate our approach, we explored a new phenotype database from biomedical ontologies and constructed Disease Manifestation Network (DMN). We combined DMN with mimMiner, which was a widely used phenotype database in disease gene prediction studies. Our approach achieved significantly improved performance over a baseline method, which used only one phenotype data source. In the leave-one-out cross-validation and de novo gene prediction analysis, our approach achieved the area under the curves of 90.7% and 90.3%, which are significantly higher than 84.2% (P < e(-4)) and 81.3% (P < e(-12)) for the baseline approach. We further demonstrated that our predicted genes have the translational potential in drug discovery. We used Crohn's disease as an example and ranked the candidate drugs based on the rank of drug targets. Our gene prediction approach prioritized druggable genes that are likely to be associated with Crohn's disease pathogenesis, and our rank of candidate drugs successfully prioritized the Food and Drug Administration-approved drugs for Crohn's disease. We also found literature evidence to support a number of drugs among the top 200 candidates. In summary, we demonstrated that a novel strategy combining unique disease phenotype data with system approaches can lead to rapid drug discovery. nlp. edu/public/data/DMN © The Author 2015. Published by Oxford University Press.

Adaptations to Climate in Candidate Genes for Common Metabolic Disorders

PubMed Central

Hancock, Angela M; Witonsky, David B; Gordon, Adam S; Eshel, Gidon; Pritchard, Jonathan K; Coop, Graham; Di Rienzo, Anna

2008-01-01

Evolutionary pressures due to variation in climate play an important role in shaping phenotypic variation among and within species and have been shown to influence variation in phenotypes such as body shape and size among humans. Genes involved in energy metabolism are likely to be central to heat and cold tolerance. To test the hypothesis that climate shaped variation in metabolism genes in humans, we used a bioinformatics approach based on network theory to select 82 candidate genes for common metabolic disorders. We genotyped 873 tag SNPs in these genes in 54 worldwide populations (including the 52 in the Human Genome Diversity Project panel) and found correlations with climate variables using rank correlation analysis and a newly developed method termed Bayesian geographic analysis. In addition, we genotyped 210 carefully matched control SNPs to provide an empirical null distribution for spatial patterns of allele frequency due to population history alone. For nearly all climate variables, we found an excess of genic SNPs in the tail of the distributions of the test statistics compared to the control SNPs, implying that metabolic genes as a group show signals of spatially varying selection. Among our strongest signals were several SNPs (e.g., LEPR R109K, FABP2 A54T) that had previously been associated with phenotypes directly related to cold tolerance. Since variation in climate may be correlated with other aspects of environmental variation, it is possible that some of the signals that we detected reflect selective pressures other than climate. Nevertheless, our results are consistent with the idea that climate has been an important selective pressure acting on candidate genes for common metabolic disorders. PMID:18282109

Genetic Predictors of Susceptibility to Cutaneous Fungal Infections: a pilot Genome Wide Association Study to Refine a Candidate Gene Search

PubMed Central

Abdel-Rahman, Susan M.; Preuett, Barry L.

2012-01-01

Background Trichophyton tonsurans is the foremost fungal pathogen of minority children in the U.S. Despite overwhelming infection rates, it does not appear that this fungus infects children in a non-specific manner. Objective This study was designed to identify genes that may predispose or protect a child from T. tonsurans infection. Methods Children participating in an earlier longitudinal study wherein infection rates could be reliably determined were eligible for inclusion. DNA from a subset (n=40) of these children at the population extremes underwent whole genome genotyping (WGG). Allele frequencies between cases and controls were examined and significant SNPs were used to develop a candidate gene list for which the remainder of the cohort (n=115) were genotyped. Cumulative infection rate was examined by genotype and the ability of selected genotypes to predict the likelihood of infection explored by multivariable analysis. Results 23 genes with a putative mechanistic role in cutaneous infection were selected for evaluation. Of these, 21 demonstrated significant differences in infection rate between genotypes. A risk index assigned to genotypes in the 21 genes accounted for over 60% of the variability observed in infection rate (adjusted r2=0.665, p<0.001). Among these, 8 appeared to account for the majority of variability that was observed (r2=0.603, p<0.001). These included genes involved in: leukocyte activation and migration, extracellular matrix integrity and remodeling, epidermal maintenance and wound repair, and cutaneous permeability. Conclusions Applying WGG to individuals at the extremes of phenotype can help to guide the selection of candidate genes in populations of small cohorts where disease etiology is likely polygenic in nature. PMID:22704677

The genome sequence of the most widely cultivated cacao type and its use to identify candidate genes regulating pod color

PubMed Central

2013-01-01

Background Theobroma cacao L. cultivar Matina 1-6 belongs to the most cultivated cacao type. The availability of its genome sequence and methods for identifying genes responsible for important cacao traits will aid cacao researchers and breeders. Results We describe the sequencing and assembly of the genome of Theobroma cacao L. cultivar Matina 1-6. The genome of the Matina 1-6 cultivar is 445 Mbp, which is significantly larger than a sequenced Criollo cultivar, and more typical of other cultivars. The chromosome-scale assembly, version 1.1, contains 711 scaffolds covering 346.0 Mbp, with a contig N50 of 84.4 kbp, a scaffold N50 of 34.4 Mbp, and an evidence-based gene set of 29,408 loci. Version 1.1 has 10x the scaffold N50 and 4x the contig N50 as Criollo, and includes 111 Mb more anchored sequence. The version 1.1 assembly has 4.4% gap sequence, while Criollo has 10.9%. Through a combination of haplotype, association mapping and gene expression analyses, we leverage this robust reference genome to identify a promising candidate gene responsible for pod color variation. We demonstrate that green/red pod color in cacao is likely regulated by the R2R3 MYB transcription factor TcMYB113, homologs of which determine pigmentation in Rosaceae, Solanaceae, and Brassicaceae. One SNP within the target site for a highly conserved trans-acting siRNA in dicots, found within TcMYB113, seems to affect transcript levels of this gene and therefore pod color variation. Conclusions We report a high-quality sequence and annotation of Theobroma cacao L. and demonstrate its utility in identifying candidate genes regulating traits. PMID:23731509

Variation in Telangiectasia Predisposing Genes Is Associated With Overall Radiation Toxicity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tanteles, George A.; Department of Cancer Studies and Molecular Medicine, University Hospitals of Leicester, Leicester Royal Infirmary, Leicester; Murray, Robert J.S.

2012-11-15

Purpose: In patients receiving radiotherapy for breast cancer where the heart is within the radiation field, cutaneous telangiectasiae could be a marker of potential radiation-induced heart disease. We hypothesized that single nucleotide polymorphisms (SNPs) in genes known to cause heritable telangiectasia-associated disorders could predispose to such late, normal tissue vascular damage. Methods and Materials: The relationship between cutaneous telangiectasia as a late normal tissue radiation injury phenotype in 633 breast cancer patients treated with radiotherapy was examined. Patients were clinically assessed for the presence of cutaneous telangiectasia and genotyped at nine SNPs in three candidate genes. Candidate SNPs were withinmore » the endoglin (ENG) and activin A receptor, type II-like 1 (ACVRL1) genes, mutations in which cause hereditary hemorrhagic telangiectasia and the ataxia-telangiectasia mutated (ATM) gene associated with ataxia-telangiectasia. Results: A total of 121 (19.1%) patients exhibited a degree of cutaneous telangiectasiae on clinical examination. Regression was used to examine the associations between the presence of telangiectasiae in patients who underwent breast-conserving surgery, controlling for the effects of boost and known brassiere size (n=388), and individual geno- or haplotypes. Inheritance of ACVRL1 SNPs marginally contributed to the risk of cutaneous telangiectasiae. Haplotypic analysis revealed a stronger association between inheritance of a ATM haplotype and the presence of cutaneous telangiectasiae, fibrosis and overall toxicity. No significant association was observed between telangiectasiae and the coinheritance of the candidate ENG SNPs. Conclusions: Genetic variation in the ATM gene influences reaction to radiotherapy through both vascular damage and increased fibrosis. The predisposing variation in the ATM gene will need to be better defined to optimize it as a predictive marker for assessing radiotherapy late effects.« less

Sleeping Beauty transposon mutagenesis identifies genes that cooperate with mutant Smad4 in gastric cancer development

PubMed Central

Takeda, Haruna; Rust, Alistair G.; Ward, Jerrold M.; Yew, Christopher Chin Kuan; Jenkins, Nancy A.; Copeland, Neal G.

2016-01-01

Mutations in SMAD4 predispose to the development of gastrointestinal cancer, which is the third leading cause of cancer-related deaths. To identify genes driving gastric cancer (GC) development, we performed a Sleeping Beauty (SB) transposon mutagenesis screen in the stomach of Smad4+/− mutant mice. This screen identified 59 candidate GC trunk drivers and a much larger number of candidate GC progression genes. Strikingly, 22 SB-identified trunk drivers are known or candidate cancer genes, whereas four SB-identified trunk drivers, including PTEN, SMAD4, RNF43, and NF1, are known human GC trunk drivers. Similar to human GC, pathway analyses identified WNT, TGF-β, and PI3K-PTEN signaling, ubiquitin-mediated proteolysis, adherens junctions, and RNA degradation in addition to genes involved in chromatin modification and organization as highly deregulated pathways in GC. Comparative oncogenomic filtering of the complete list of SB-identified genes showed that they are highly enriched for genes mutated in human GC and identified many candidate human GC genes. Finally, by comparing our complete list of SB-identified genes against the list of mutated genes identified in five large-scale human GC sequencing studies, we identified LDL receptor-related protein 1B (LRP1B) as a previously unidentified human candidate GC tumor suppressor gene. In LRP1B, 129 mutations were found in 462 human GC samples sequenced, and LRP1B is one of the top 10 most deleted genes identified in a panel of 3,312 human cancers. SB mutagenesis has, thus, helped to catalog the cooperative molecular mechanisms driving SMAD4-induced GC growth and discover genes with potential clinical importance in human GC. PMID:27006499

Sleeping Beauty transposon mutagenesis identifies genes that cooperate with mutant Smad4 in gastric cancer development.

PubMed

Takeda, Haruna; Rust, Alistair G; Ward, Jerrold M; Yew, Christopher Chin Kuan; Jenkins, Nancy A; Copeland, Neal G

2016-04-05

Mutations in SMAD4 predispose to the development of gastrointestinal cancer, which is the third leading cause of cancer-related deaths. To identify genes driving gastric cancer (GC) development, we performed a Sleeping Beauty (SB) transposon mutagenesis screen in the stomach of Smad4(+/-) mutant mice. This screen identified 59 candidate GC trunk drivers and a much larger number of candidate GC progression genes. Strikingly, 22 SB-identified trunk drivers are known or candidate cancer genes, whereas four SB-identified trunk drivers, including PTEN, SMAD4, RNF43, and NF1, are known human GC trunk drivers. Similar to human GC, pathway analyses identified WNT, TGF-β, and PI3K-PTEN signaling, ubiquitin-mediated proteolysis, adherens junctions, and RNA degradation in addition to genes involved in chromatin modification and organization as highly deregulated pathways in GC. Comparative oncogenomic filtering of the complete list of SB-identified genes showed that they are highly enriched for genes mutated in human GC and identified many candidate human GC genes. Finally, by comparing our complete list of SB-identified genes against the list of mutated genes identified in five large-scale human GC sequencing studies, we identified LDL receptor-related protein 1B (LRP1B) as a previously unidentified human candidate GC tumor suppressor gene. In LRP1B, 129 mutations were found in 462 human GC samples sequenced, and LRP1B is one of the top 10 most deleted genes identified in a panel of 3,312 human cancers. SB mutagenesis has, thus, helped to catalog the cooperative molecular mechanisms driving SMAD4-induced GC growth and discover genes with potential clinical importance in human GC.

Genetics of primary ovarian insufficiency: new developments and opportunities

PubMed Central

Qin, Yingying; Jiao, Xue; Simpson, Joe Leigh; Chen, Zi-Jiang

2015-01-01

BACKGROUND Primary ovarian insufficiency (POI) is characterized by marked heterogeneity, but with a significant genetic contribution. Identifying exact causative genes has been challenging, with many discoveries not replicated. It is timely to take stock of the field, outlining the progress made, framing the controversies and anticipating future directions in elucidating the genetics of POI. METHODS A search for original articles published up to May 2015 was performed using PubMed and Google Scholar, identifying studies on the genetic etiology of POI. Studies were included if chromosomal analysis, candidate gene screening and a genome-wide study were conducted. Articles identified were restricted to English language full-text papers. RESULTS Chromosomal abnormalities have long been recognized as a frequent cause of POI, with a currently estimated prevalence of 10–13%. Using the traditional karyotype methodology, monosomy X, mosaicism, X chromosome deletions and rearrangements, X-autosome translocations, and isochromosomes have been detected. Based on candidate gene studies, single gene perturbations unequivocally having a deleterious effect in at least one population include Bone morphogenetic protein 15 (BMP15), Progesterone receptor membrane component 1 (PGRMC1), and Fragile X mental retardation 1 (FMR1) premutation on the X chromosome; Growth differentiation factor 9 (GDF9), Folliculogenesis specific bHLH transcription factor (FIGLA), Newborn ovary homeobox gene (NOBOX), Nuclear receptor subfamily 5, group A, member 1 (NR5A1) and Nanos homolog 3 (NANOS3) seem likely as well, but mostly being found in no more than 1–2% of a single population studied. Whole genome approaches have utilized genome-wide association studies (GWAS) to reveal loci not predicted on the basis of a candidate gene, but it remains difficult to locate causative genes and susceptible loci were not always replicated. Cytogenomic methods (array CGH) have identified other regions of interest but studies have not shown consistent results, the resolution of arrays has varied and replication is uncommon. Whole-exome sequencing in non-syndromic POI kindreds has only recently begun, revealing mutations in the Stromal antigen 3 (STAG3), Synaptonemal complex central element 1 (SYCE1), minichromosome maintenance complex component 8 and 9 (MCM8, MCM9) and ATP-dependent DNA helicase homolog (HFM1) genes. Given the slow progress in candidate-gene analysis and relatively small sample sizes available for GWAS, family-based whole exome and whole genome sequencing appear to be the most promising approaches for detecting potential genes responsible for POI. CONCLUSION Taken together, the cytogenetic, cytogenomic (array CGH) and exome sequencing approaches have revealed a genetic causation in ∼20–25% of POI cases. Uncovering the remainder of the causative genes will be facilitated not only by whole genome approaches involving larger cohorts in multiple populations but also incorporating environmental exposures and exploring signaling pathways in intragenic and intergenic regions that point to perturbations in regulatory genes and networks. PMID:26243799

Discovering mutated driver genes through a robust and sparse co-regularized matrix factorization framework with prior information from mRNA expression patterns and interaction network.

PubMed

Xi, Jianing; Wang, Minghui; Li, Ao

2018-06-05

Discovery of mutated driver genes is one of the primary objective for studying tumorigenesis. To discover some relatively low frequently mutated driver genes from somatic mutation data, many existing methods incorporate interaction network as prior information. However, the prior information of mRNA expression patterns are not exploited by these existing network-based methods, which is also proven to be highly informative of cancer progressions. To incorporate prior information from both interaction network and mRNA expressions, we propose a robust and sparse co-regularized nonnegative matrix factorization to discover driver genes from mutation data. Furthermore, our framework also conducts Frobenius norm regularization to overcome overfitting issue. Sparsity-inducing penalty is employed to obtain sparse scores in gene representations, of which the top scored genes are selected as driver candidates. Evaluation experiments by known benchmarking genes indicate that the performance of our method benefits from the two type of prior information. Our method also outperforms the existing network-based methods, and detect some driver genes that are not predicted by the competing methods. In summary, our proposed method can improve the performance of driver gene discovery by effectively incorporating prior information from interaction network and mRNA expression patterns into a robust and sparse co-regularized matrix factorization framework.

Identification of Candidate Genes Responsible for Stem Pith Production Using Expression Analysis in Solid-Stemmed Wheat.

PubMed

Oiestad, A J; Martin, J M; Cook, J; Varella, A C; Giroux, M J

2017-07-01

The wheat stem sawfly (WSS) is an economically important pest of wheat in the Northern Great Plains. The primary means of WSS control is resistance associated with the single quantitative trait locus (QTL) , which controls most stem solidness variation. The goal of this study was to identify stem solidness candidate genes via RNA-seq. This study made use of 28 single nucleotide polymorphism (SNP) makers derived from expressed sequence tags (ESTs) linked to contained within a 5.13 cM region. Allele specific expression of EST markers was examined in stem tissue for solid and hollow-stemmed pairs of two spring wheat near isogenic lines (NILs) differing for the QTL. Of the 28 ESTs, 13 were located within annotated genes and 10 had detectable stem expression. Annotated genes corresponding to four of the ESTs were differentially expressed between solid and hollow-stemmed NILs and represent possible stem solidness gene candidates. Further examination of the 5.13 cM region containing the 28 EST markers identified 260 annotated genes. Twenty of the 260 linked genes were up-regulated in hollow NIL stems, while only seven genes were up-regulated in solid NIL stems. An -methyltransferase within the region of interest was identified as a candidate based on differential expression between solid and hollow-stemmed NILs and putative function. Further study of these candidate genes may lead to the identification of the gene(s) controlling stem solidness and an increased ability to select for wheat stem solidness and manage WSS. Copyright © 2017 Crop Science Society of America.

PCR-based detection of gene transfer vectors: application to gene doping surveillance.

PubMed

Perez, Irene C; Le Guiner, Caroline; Ni, Weiyi; Lyles, Jennifer; Moullier, Philippe; Snyder, Richard O

2013-12-01

Athletes who illicitly use drugs to enhance their athletic performance are at risk of being banned from sports competitions. Consequently, some athletes may seek new doping methods that they expect to be capable of circumventing detection. With advances in gene transfer vector design and therapeutic gene transfer, and demonstrations of safety and therapeutic benefit in humans, there is an increased probability of the pursuit of gene doping by athletes. In anticipation of the potential for gene doping, assays have been established to directly detect complementary DNA of genes that are top candidates for use in doping, as well as vector control elements. The development of molecular assays that are capable of exposing gene doping in sports can serve as a deterrent and may also identify athletes who have illicitly used gene transfer for performance enhancement. PCR-based methods to detect foreign DNA with high reliability, sensitivity, and specificity include TaqMan real-time PCR, nested PCR, and internal threshold control PCR.

Systems genetics of intravenous cocaine self-administration in the BXD recombinant inbred mouse panel

PubMed Central

Dickson, Price E.; Miller, Mellessa M.; Calton, Michele A.; Bubier, Jason A.; Cook, Melloni N.; Goldowitz, Daniel; Chesler, Elissa J.; Mittleman, Guy

2015-01-01

Rationale Cocaine addiction is a major public health problem with a substantial genetic basis for which the biological mechanisms remain largely unknown. Systems genetics is a powerful method for discovering novel mechanisms underlying complex traits, and intravenous drug self-administration (IVSA) is the gold standard for assessing volitional drug use in preclinical studies. We have integrated these approaches to identify novel genes and networks underling cocaine use in mice. Methods Mice from 39 BXD strains acquired cocaine IVSA (0.56 mg/kg/infusion). Mice from 29 BXD strains completed a full dose-response curve (0.032 – 1.8 mg/kg/infusion). Results We identified independent genetic correlations between cocaine IVSA and measures of environmental exploration and cocaine sensitization. We identified genome-wide significant QTL on chromosomes 7 and 11 associated with shifts in the dose-response curve and on chromosome 16 associated with sessions to acquire cocaine IVSA. Using publicly available gene expression data from the nucleus accumbens, midbrain, and prefrontal cortex of drug-naïve mice, we identified Aplp1 and Cyfip2 as positional candidates underlying the behavioral QTL on chromosomes 7 and 11, respectively. A genome-wide significant trans-eQTL linking Fam53b (a GWAS candidate for human cocaine dependence) on chromosome 7 to the cocaine IVSA behavioral QTL on chromosome 11 was identified in the midbrain; Fam53b and Cyfip2 were co-expressed genome-wide significantly in the midbrain. This finding indicates that cocaine IVSA studies using mice can identify genes involved in human cocaine use. Conclusions These data provide novel candidate genes underlying cocaine IVSA in mice, and suggest mechanisms driving human cocaine use. PMID:26581503

Reference gene selection for molecular studies of dormancy in wild oat (Avena fatua L.) caryopses by RT-qPCR method.

PubMed

Ruduś, Izabela; Kępczyński, Jan

2018-01-01

Molecular studies of primary and secondary dormancy in Avena fatua L., a serious weed of cereal and other crops, are intended to reveal the species-specific details of underlying molecular mechanisms which in turn may be useable in weed management. Among others, quantitative real-time PCR (RT-qPCR) data of comparative gene expression analysis may give some insight into the involvement of particular wild oat genes in dormancy release, maintenance or induction by unfavorable conditions. To assure obtaining biologically significant results using this method, the expression stability of selected candidate reference genes in different data subsets was evaluated using four statistical algorithms i.e. geNorm, NormFinder, Best Keeper and ΔCt method. Although some discrepancies in their ranking outputs were noticed, evidently two ubiquitin-conjugating enzyme homologs, AfUBC1 and AfUBC2, as well as one homolog of glyceraldehyde 3-phosphate dehydrogenase AfGAPDH1 and TATA-binding protein AfTBP2 appeared as more stably expressed than AfEF1a (translation elongation factor 1α), AfGAPDH2 or the least stable α-tubulin homolog AfTUA1 in caryopses and seedlings of A. fatua. Gene expression analysis of a dormancy-related wild oat transcription factor VIVIPAROUS1 (AfVP1) allowed for a validation of candidate reference genes performance. Based on the obtained results it can be recommended that the normalization factor calculated as a geometric mean of Cq values of AfUBC1, AfUBC2 and AfGAPDH1 would be optimal for RT-qPCR results normalization in the experiments comprising A. fatua caryopses of different dormancy status.

Candidate genes that have facilitated freshwater adaptation by palaemonid prawns in the genus Macrobrachium: identification and expression validation in a model species (M. koombooloomba)

PubMed Central

Amin, Shorash; Mather, Peter B.; Hurwood, David A.

2017-01-01

Background The endemic Australian freshwater prawn, Macrobrachium koombooloomba, provides a model for exploring genes involved with freshwater adaptation because it is one of the relatively few Macrobrachium species that can complete its entire life cycle in freshwater. Methods The present study was conducted to identify potential candidate genes that are likely to contribute to effective freshwater adaptation by M. koombooloomba using a transcriptomics approach. De novo assembly of 75 bp paired end 227,564,643 high quality Illumina raw reads from 6 different cDNA libraries revealed 125,917 contigs of variable lengths (200–18,050 bp) with an N50 value of 1597. Results In total, 31,272 (24.83%) of the assembled contigs received significant blast hits, of which 27,686 and 22,560 contigs were mapped and functionally annotated, respectively. CEGMA (Core Eukaryotic Genes Mapping Approach) based transcriptome quality assessment revealed 96.37% completeness. We identified 43 different potential genes that are likely to be involved with freshwater adaptation in M. koombooloomba. Identified candidate genes included: 25 genes for osmoregulation, five for cell volume regulation, seven for stress tolerance, three for body fluid (haemolymph) maintenance, eight for epithelial permeability and water channel regulation, nine for egg size control and three for larval development. RSEM (RNA-Seq Expectation Maximization) based abundance estimation revealed that 6,253, 5,753 and 3,795 transcripts were expressed (at TPM value ≥10) in post larvae, juveniles and adults, respectively. Differential gene expression (DGE) analysis showed that 15 genes were expressed differentially in different individuals but these genes apparently were not involved with freshwater adaptation but rather were involved in growth, development and reproductive maturation. Discussion The genomic resources developed here will be useful for better understanding the molecular basis of freshwater adaptation in Macrobrachium prawns and other crustaceans more broadly. PMID:28194319

Genome-Wide Identification of Regulatory Elements and Reconstruction of Gene Regulatory Networks of the Green Alga Chlamydomonas reinhardtii under Carbon Deprivation

PubMed Central

Vischi Winck, Flavia; Arvidsson, Samuel; Riaño-Pachón, Diego Mauricio; Hempel, Sabrina; Koseska, Aneta; Nikoloski, Zoran; Urbina Gomez, David Alejandro; Rupprecht, Jens; Mueller-Roeber, Bernd

2013-01-01

The unicellular green alga Chlamydomonas reinhardtii is a long-established model organism for studies on photosynthesis and carbon metabolism-related physiology. Under conditions of air-level carbon dioxide concentration [CO2], a carbon concentrating mechanism (CCM) is induced to facilitate cellular carbon uptake. CCM increases the availability of carbon dioxide at the site of cellular carbon fixation. To improve our understanding of the transcriptional control of the CCM, we employed FAIRE-seq (formaldehyde-assisted Isolation of Regulatory Elements, followed by deep sequencing) to determine nucleosome-depleted chromatin regions of algal cells subjected to carbon deprivation. Our FAIRE data recapitulated the positions of known regulatory elements in the promoter of the periplasmic carbonic anhydrase (Cah1) gene, which is upregulated during CCM induction, and revealed new candidate regulatory elements at a genome-wide scale. In addition, time series expression patterns of 130 transcription factor (TF) and transcription regulator (TR) genes were obtained for cells cultured under photoautotrophic condition and subjected to a shift from high to low [CO2]. Groups of co-expressed genes were identified and a putative directed gene-regulatory network underlying the CCM was reconstructed from the gene expression data using the recently developed IOTA (inner composition alignment) method. Among the candidate regulatory genes, two members of the MYB-related TF family, Lcr1 (Low-CO 2 response regulator 1) and Lcr2 (Low-CO 2 response regulator 2), may play an important role in down-regulating the expression of a particular set of TF and TR genes in response to low [CO2]. The results obtained provide new insights into the transcriptional control of the CCM and revealed more than 60 new candidate regulatory genes. Deep sequencing of nucleosome-depleted genomic regions indicated the presence of new, previously unknown regulatory elements in the C. reinhardtii genome. Our work can serve as a basis for future functional studies of transcriptional regulator genes and genomic regulatory elements in Chlamydomonas. PMID:24224019

Candidacy of a chitin-inducible gibberellin-responsive gene for a major locus affecting plant height in rice that is closely linked to Green Revolution gene sd1.

PubMed

Kovi, Mallikarjuna Rao; Zhang, Yushan; Yu, Sibin; Yang, Gaiyu; Yan, Wenhao; Xing, Yongzhong

2011-09-01

Appropriate plant height is crucial for lodging resistance to improve the rice crop yield. The application of semi-dwarf 1 led to the green revolution in the 1960s, by predominantly increasing the rice yield. However, the frequent use of single sd1 gene sources may cause genetic vulnerability to pests and diseases. Identifying useful novel semi-dwarf genes is important for the genetic manipulation of plant architecture in practical rice breeding. In this study, introgression lines derived from two parents contrasting in plant height, Zhenshan 97 and Pokkali were employed to locate a gene with a large effect on plant height by the bulk segregant analysis method. A major gene, ph1, was mapped to a region closely linked to sd1 on chromosome 1; the additive effects of ph1 were more than 50 cm on the plant height and 2 days on the heading date in a BC(4)F(2) population and its progeny. ph1 was then fine mapped to BAC AP003227. Gene annotation indicated that LOC_OS01g65990 encoding a chitin-inducible gibberellin-responsive protein (CIGR), which belongs to the GRAS family, might be the right candidate gene of ph1. Co-segregation analysis of the candidate gene-derived marker finally confirmed its identity as the candidate gene. A higher expression level of the CIGR was detected in all the tested tissues in tall plants compared to those of short plants, especially in the young leaf sheath containing elongating tissues, which indicated its importance role in regulating plant height. ph1 showed a tremendous genetic effect on plant height, which is distinct from sd1 and could be a new resource for breeding semi-dwarf varieties.

Survey of candidate genes for maize resistance to infection by Aspergillus flavus and/or aflatoxin contamination

Treesearch

Leigh Hawkins; Marilyn Warburton; Juliet Tang; John Tomashek; Dafne Alves Oliveira; Oluwaseun Ogunola; J. Smith; W. Williams

2018-01-01

Many projects have identified candidate genes for resistance to aflatoxin accumulation or Aspergillus flavus infection and growth in maize using genetic mapping, genomics, transcriptomics and/or proteomics studies. However, only a small percentage of these candidates have been validated in field conditions, and their relative contribution to...

Validating internal controls for quantitative plant gene expression studies.

PubMed

Brunner, Amy M; Yakovlev, Igor A; Strauss, Steven H

2004-08-18

Real-time reverse transcription PCR (RT-PCR) has greatly improved the ease and sensitivity of quantitative gene expression studies. However, accurate measurement of gene expression with this method relies on the choice of a valid reference for data normalization. Studies rarely verify that gene expression levels for reference genes are adequately consistent among the samples used, nor compare alternative genes to assess which are most reliable for the experimental conditions analyzed. Using real-time RT-PCR to study the expression of 10 poplar (genus Populus) housekeeping genes, we demonstrate a simple method for determining the degree of stability of gene expression over a set of experimental conditions. Based on a traditional method for analyzing the stability of varieties in plant breeding, it defines measures of gene expression stability from analysis of variance (ANOVA) and linear regression. We found that the potential internal control genes differed widely in their expression stability over the different tissues, developmental stages and environmental conditions studied. Our results support that quantitative comparisons of candidate reference genes are an important part of real-time RT-PCR studies that seek to precisely evaluate variation in gene expression. The method we demonstrated facilitates statistical and graphical evaluation of gene expression stability. Selection of the best reference gene for a given set of experimental conditions should enable detection of biologically significant changes in gene expression that are too small to be revealed by less precise methods, or when highly variable reference genes are unknowingly used in real-time RT-PCR experiments.

Cumulative Genetic Risk Predicts Platinum/Taxane-Induced Neurotoxicity

PubMed Central

McWhinney-Glass, Sarah; Winham, Stacey J.; Hertz, Daniel L.; Revollo, Jane Yen; Paul, Jim; He, Yijing; Brown, Robert; Motsinger-Reif, Alison A.; McLeod, Howard L.

2013-01-01

Purpose The combination of a platinum and taxane are standard of care for many cancers, but the utility is often limited due to debilitating neurotoxicity. We examined whether single nucleotide polymorphisms (SNPs) from annotated candidate genes will identify genetic risk for chemotherapy-induced neurotoxicity. Patients and Methods A candidate-gene association study was conducted to validate the relevance of 1261 SNPs within 60 candidate genes in 404 ovarian cancer patients receiving platinum/taxane chemotherapy on the SCOTROC1 trial. Statistically significant variants were then assessed for replication in a separate 404 patient replication cohort from SCOTROC1. Results Significant associations with chemotherapy-induced neurotoxicity were identified and replicated for four SNPs in SOX10, BCL2, OPRM1, and TRPV1. The Population Attributable Risk for each of the four SNPs ranged from 5–35%, with a cumulative risk of 62%. According to the multiplicative model, the odds of developing neurotoxicity increase by a factor of 1.64 for every risk genotype. Patients possessing 3 risk variants have an estimated odds ratio of 4.49 (2.36–8.54) compared to individuals with 0 risk variants. Neither the four SNPs nor the risk score were associated with progression free survival or overall survival. Conclusions This study demonstrates that SNPs in four genes have a significant cumulative association with increased risk for the development of chemotherapy-induced neurotoxicity, independent of patient survival. PMID:23963862

A comparative analysis of genetic diversity of candidate genes associated with type 2 diabetes in worldwide populations.

PubMed

Gong, Xian; Zhang, Chao; Yiliyasi·Aisa, Yiliyasi·Aisa; Shi, Ying; Yang, Xue-wei; NuersimanguliAosiman, NuersimanguliAosiman; Guan, Ya-qun; Xu, Shu-hua

2016-06-20

Over the last decade, a larger number of type 2 diabetes mellitus (T2DM) susceptible candidate genes have been reported by numerous genome-wide association studies (GWAS). Understanding the genetic diversity of these candidate genes among worldwide populations not only facilitates to elucidating the genetic mechanism of T2DM, but also provides guidance to further studies of pathogenesis of T2DM in any certain population. In this study, we identified 170 genes or genomic regions associated with T2DM by searching the GWAS databases and related literatures. We next analyzed the genetic diversity of these genes (or genomic regions) among present-day human populations by curetting the 1000 Genomes Projects phase1 dataset covering 14 worldwide populations. We further compared the characteristics of T2DM genes in different populations. No significant differences of genetic diversity were observed among the 14 worldwide populations between the T2DM candidate genes and the non-T2DM genes in terms of overall pattern. However, we observed some genes, such as IL20RA, RNMTL1-NXN, NOTCH2, ADRA2A-BTBD7P2, TBC1D4, RBM38-HMGB1P1, UBE2E2, and PPARD, show considerable differentiation between populations. In particular, IL20RA (FST=0.1521) displays the greatest population difference which is mainly contributed by that between Africans and non-Africans. Moreover, we revealed genetic differences between East Asians and Europeans on some candidate genes such as DGKB-AGMO (FST=0.173) and JAZF1 (FST=0.182). Our results indicate that some T2DM susceptible candidate genes harbor highly-differentiated variants between populations. These analyses, despite preliminary, should advance our understanding of the population difference of susceptibility to T2DM and provide insightful reference that future studies can relay on.

Selection of reference genes for RT-qPCR analysis in a predatory biological control agent, Coleomegilla maculata (Coleoptera: Coccinellidae).

PubMed

Yang, Chunxiao; Pan, Huipeng; Noland, Jeffrey Edward; Zhang, Deyong; Zhang, Zhanhong; Liu, Yong; Zhou, Xuguo

2015-12-10

Reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) is a reliable technique for quantifying gene expression across various biological processes, of which requires a set of suited reference genes to normalize the expression data. Coleomegilla maculata (Coleoptera: Coccinellidae), is one of the most extensively used biological control agents in the field to manage arthropod pest species. In this study, expression profiles of 16 housekeeping genes selected from C. maculata were cloned and investigated. The performance of these candidates as endogenous controls under specific experimental conditions was evaluated by dedicated algorithms, including geNorm, Normfinder, BestKeeper, and ΔCt method. In addition, RefFinder, a comprehensive platform integrating all the above-mentioned algorithms, ranked the overall stability of these candidate genes. As a result, various sets of suitable reference genes were recommended specifically for experiments involving different tissues, developmental stages, sex, and C. maculate larvae treated with dietary double stranded RNA. This study represents the critical first step to establish a standardized RT-qPCR protocol for the functional genomics research in a ladybeetle C. maculate. Furthermore, it lays the foundation for conducting ecological risk assessment of RNAi-based gene silencing biotechnologies on non-target organisms; in this case, a key predatory biological control agent.

Analysis of 30 Genes (355 SNPS) Related to Energy Homeostasis for Association with Adiposity in European-American and Yup'ik Eskimo Populations

PubMed Central

Chung, Wendy K.; Patki, Amit; Matsuoka, Naoki; Boyer, Bert B.; Liu, Nianjun; Musani, Solomon K.; Goropashnaya, Anna V.; Tan, Perciliz L.; Katsanis, Nicholas; Johnson, Stephen B.; Gregersen, Peter K.; Allison, David B.; Leibel, Rudolph L.; Tiwari, Hemant K.

2009-01-01

Objective Human adiposity is highly heritable, but few of the genes that predispose to obesity in most humans are known. We tested candidate genes in pathways related to food intake and energy expenditure for association with measures of adiposity. Methods We studied 355 genetic variants in 30 candidate genes in 7 molecular pathways related to obesity in two groups of adult subjects: 1,982 unrelated European Americans living in the New York metropolitan area drawn from the extremes of their body mass index (BMI) distribution and 593 related Yup'ik Eskimos living in rural Alaska characterized for BMI, body composition, waist circumference, and skin fold thicknesses. Data were analyzed by using a mixed model in conjunction with a false discovery rate (FDR) procedure to correct for multiple testing. Results After correcting for multiple testing, two single nucleotide polymorphisms (SNPs) in Ghrelin (GHRL) (rs35682 and rs35683) were associated with BMI in the New York European Americans. This association was not replicated in the Yup'ik participants. There was no evidence for gene × gene interactions among genes within the same molecular pathway after adjusting for multiple testing via FDR control procedure. Conclusion Genetic variation in GHRL may have a modest impact on BMI in European Americans. PMID:19077438

Identification of Immunity Related Genes to Study the Physalis peruviana – Fusarium oxysporum Pathosystem

PubMed Central

Enciso-Rodríguez, Felix E.; González, Carolina; Rodríguez, Edwin A.; López, Camilo E.; Landsman, David; Barrero, Luz Stella; Mariño-Ramírez, Leonardo

2013-01-01

The Cape gooseberry ( Physalis peruviana L) is an Andean exotic fruit with high nutritional value and appealing medicinal properties. However, its cultivation faces important phytosanitary problems mainly due to pathogens like Fusarium oxysporum, Cercosporaphysalidis and Alternaria spp. Here we used the Cape gooseberry foliar transcriptome to search for proteins that encode conserved domains related to plant immunity including: NBS (Nucleotide Binding Site), CC (Coiled-Coil), TIR (Toll/Interleukin-1 Receptor). We identified 74 immunity related gene candidates in P . peruviana which have the typical resistance gene (R-gene) architecture, 17 Receptor like kinase (RLKs) candidates related to PAMP-Triggered Immunity (PTI), eight (TIR-NBS-LRR, or TNL) and nine (CC–NBS-LRR, or CNL) candidates related to Effector-Triggered Immunity (ETI) genes among others. These candidate genes were categorized by molecular function (98%), biological process (85%) and cellular component (79%) using gene ontology. Some of the most interesting predicted roles were those associated with binding and transferase activity. We designed 94 primers pairs from the 74 immunity-related genes (IRGs) to amplify the corresponding genomic regions on six genotypes that included resistant and susceptible materials. From these, we selected 17 single band amplicons and sequenced them in 14 F. oxysporum resistant and susceptible genotypes. Sequence polymorphisms were analyzed through preliminary candidate gene association, which allowed the detection of one SNP at the PpIRG-63 marker revealing a nonsynonymous mutation in the predicted LRR domain suggesting functional roles for resistance. PMID:23844210

Identification of immunity related genes to study the Physalis peruviana--Fusarium oxysporum pathosystem.

PubMed

Enciso-Rodríguez, Felix E; González, Carolina; Rodríguez, Edwin A; López, Camilo E; Landsman, David; Barrero, Luz Stella; Mariño-Ramírez, Leonardo

2013-01-01

The Cape gooseberry (Physalisperuviana L) is an Andean exotic fruit with high nutritional value and appealing medicinal properties. However, its cultivation faces important phytosanitary problems mainly due to pathogens like Fusarium oxysporum, Cercosporaphysalidis and Alternaria spp. Here we used the Cape gooseberry foliar transcriptome to search for proteins that encode conserved domains related to plant immunity including: NBS (Nucleotide Binding Site), CC (Coiled-Coil), TIR (Toll/Interleukin-1 Receptor). We identified 74 immunity related gene candidates in P. peruviana which have the typical resistance gene (R-gene) architecture, 17 Receptor like kinase (RLKs) candidates related to PAMP-Triggered Immunity (PTI), eight (TIR-NBS-LRR, or TNL) and nine (CC-NBS-LRR, or CNL) candidates related to Effector-Triggered Immunity (ETI) genes among others. These candidate genes were categorized by molecular function (98%), biological process (85%) and cellular component (79%) using gene ontology. Some of the most interesting predicted roles were those associated with binding and transferase activity. We designed 94 primers pairs from the 74 immunity-related genes (IRGs) to amplify the corresponding genomic regions on six genotypes that included resistant and susceptible materials. From these, we selected 17 single band amplicons and sequenced them in 14 F. oxysporum resistant and susceptible genotypes. Sequence polymorphisms were analyzed through preliminary candidate gene association, which allowed the detection of one SNP at the PpIRG-63 marker revealing a nonsynonymous mutation in the predicted LRR domain suggesting functional roles for resistance.

Next-generation sequencing for identification of candidate genes for Fusarium wilt and sterility mosaic disease in pigeonpea (Cajanus cajan).

PubMed

Singh, Vikas K; Khan, Aamir W; Saxena, Rachit K; Kumar, Vinay; Kale, Sandip M; Sinha, Pallavi; Chitikineni, Annapurna; Pazhamala, Lekha T; Garg, Vanika; Sharma, Mamta; Sameer Kumar, Chanda Venkata; Parupalli, Swathi; Vechalapu, Suryanarayana; Patil, Suyash; Muniswamy, Sonnappa; Ghanta, Anuradha; Yamini, Kalinati Narasimhan; Dharmaraj, Pallavi Subbanna; Varshney, Rajeev K

2016-05-01

To map resistance genes for Fusarium wilt (FW) and sterility mosaic disease (SMD) in pigeonpea, sequencing-based bulked segregant analysis (Seq-BSA) was used. Resistant (R) and susceptible (S) bulks from the extreme recombinant inbred lines of ICPL 20096 × ICPL 332 were sequenced. Subsequently, SNP index was calculated between R- and S-bulks with the help of draft genome sequence and reference-guided assembly of ICPL 20096 (resistant parent). Seq-BSA has provided seven candidate SNPs for FW and SMD resistance in pigeonpea. In parallel, four additional genotypes were re-sequenced and their combined analysis with R- and S-bulks has provided a total of 8362 nonsynonymous (ns) SNPs. Of 8362 nsSNPs, 60 were found within the 2-Mb flanking regions of seven candidate SNPs identified through Seq-BSA. Haplotype analysis narrowed down to eight nsSNPs in seven genes. These eight nsSNPs were further validated by re-sequencing 11 genotypes that are resistant and susceptible to FW and SMD. This analysis revealed association of four candidate nsSNPs in four genes with FW resistance and four candidate nsSNPs in three genes with SMD resistance. Further, In silico protein analysis and expression profiling identified two most promising candidate genes namely C.cajan_01839 for SMD resistance and C.cajan_03203 for FW resistance. Identified candidate genomic regions/SNPs will be useful for genomics-assisted breeding in pigeonpea. © 2015 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

Interval mapping for red/green skin color in Asian pears using a modified QTL-seq method

PubMed Central

Xue, Huabai; Shi, Ting; Wang, Fangfang; Zhou, Huangkai; Yang, Jian; Wang, Long; Wang, Suke; Su, Yanli; Zhang, Zhen; Qiao, Yushan; Li, Xiugen

2017-01-01

Pears with red skin are attractive to consumers and provide additional health benefits. Identification of the gene(s) responsible for skin coloration can benefit cultivar selection and breeding. The use of QTL-seq, a bulked segregant analysis method, can be problematic when heterozygous parents are involved. The present study modified the QTL-seq method by introducing a |Δ(SNP-index)| parameter to improve the accuracy of mapping the red skin trait in a group of highly heterozygous Asian pears. The analyses were based on mixed DNA pools composed of 28 red-skinned and 27 green-skinned pear lines derived from a cross between the ‘Mantianhong’ and ‘Hongxiangsu’ red-skinned cultivars. The ‘Dangshansuli’ cultivar genome was used as reference for sequence alignment. An average single-nucleotide polymorphism (SNP) index was calculated using a sliding window approach (200-kb windows, 20-kb increments). Nine scaffolds within the candidate QTL interval were in the fifth linkage group from 111.9 to 177.1 cM. There was a significant linkage between the insertions/deletions and simple sequence repeat markers designed from the candidate intervals and the red/green skin (R/G) locus, which was in a 582.5-kb candidate interval that contained 81 predicted protein-coding gene models and was composed of two subintervals at the bottom of the fifth chromosome. The ZFRI 130-16, In2130-12 and In2130-16 markers located near the R/G locus could potentially be used to identify the red skin trait in Asian pear populations. This study provides new insights into the genetics controlling the red skin phenotype in this fruit. PMID:29118994

Interval mapping for red/green skin color in Asian pears using a modified QTL-seq method.

PubMed

Xue, Huabai; Shi, Ting; Wang, Fangfang; Zhou, Huangkai; Yang, Jian; Wang, Long; Wang, Suke; Su, Yanli; Zhang, Zhen; Qiao, Yushan; Li, Xiugen

2017-01-01

Pears with red skin are attractive to consumers and provide additional health benefits. Identification of the gene(s) responsible for skin coloration can benefit cultivar selection and breeding. The use of QTL-seq, a bulked segregant analysis method, can be problematic when heterozygous parents are involved. The present study modified the QTL-seq method by introducing a |Δ(SNP-index)| parameter to improve the accuracy of mapping the red skin trait in a group of highly heterozygous Asian pears. The analyses were based on mixed DNA pools composed of 28 red-skinned and 27 green-skinned pear lines derived from a cross between the 'Mantianhong' and 'Hongxiangsu' red-skinned cultivars. The 'Dangshansuli' cultivar genome was used as reference for sequence alignment. An average single-nucleotide polymorphism (SNP) index was calculated using a sliding window approach (200-kb windows, 20-kb increments). Nine scaffolds within the candidate QTL interval were in the fifth linkage group from 111.9 to 177.1 cM. There was a significant linkage between the insertions/deletions and simple sequence repeat markers designed from the candidate intervals and the red/green skin (R/G) locus, which was in a 582.5-kb candidate interval that contained 81 predicted protein-coding gene models and was composed of two subintervals at the bottom of the fifth chromosome. The ZFRI 130-16, In2130-12 and In2130-16 markers located near the R/G locus could potentially be used to identify the red skin trait in Asian pear populations. This study provides new insights into the genetics controlling the red skin phenotype in this fruit.

ICan: an integrated co-alteration network to identify ovarian cancer-related genes.

PubMed

Zhou, Yuanshuai; Liu, Yongjing; Li, Kening; Zhang, Rui; Qiu, Fujun; Zhao, Ning; Xu, Yan

2015-01-01

Over the last decade, an increasing number of integrative studies on cancer-related genes have been published. Integrative analyses aim to overcome the limitation of a single data type, and provide a more complete view of carcinogenesis. The vast majority of these studies used sample-matched data of gene expression and copy number to investigate the impact of copy number alteration on gene expression, and to predict and prioritize candidate oncogenes and tumor suppressor genes. However, correlations between genes were neglected in these studies. Our work aimed to evaluate the co-alteration of copy number, methylation and expression, allowing us to identify cancer-related genes and essential functional modules in cancer. We built the Integrated Co-alteration network (ICan) based on multi-omics data, and analyzed the network to uncover cancer-related genes. After comparison with random networks, we identified 155 ovarian cancer-related genes, including well-known (TP53, BRCA1, RB1 and PTEN) and also novel cancer-related genes, such as PDPN and EphA2. We compared the results with a conventional method: CNAmet, and obtained a significantly better area under the curve value (ICan: 0.8179, CNAmet: 0.5183). In this paper, we describe a framework to find cancer-related genes based on an Integrated Co-alteration network. Our results proved that ICan could precisely identify candidate cancer genes and provide increased mechanistic understanding of carcinogenesis. This work suggested a new research direction for biological network analyses involving multi-omics data.

ICan: An Integrated Co-Alteration Network to Identify Ovarian Cancer-Related Genes

PubMed Central

Zhou, Yuanshuai; Liu, Yongjing; Li, Kening; Zhang, Rui; Qiu, Fujun; Zhao, Ning; Xu, Yan

2015-01-01

Background Over the last decade, an increasing number of integrative studies on cancer-related genes have been published. Integrative analyses aim to overcome the limitation of a single data type, and provide a more complete view of carcinogenesis. The vast majority of these studies used sample-matched data of gene expression and copy number to investigate the impact of copy number alteration on gene expression, and to predict and prioritize candidate oncogenes and tumor suppressor genes. However, correlations between genes were neglected in these studies. Our work aimed to evaluate the co-alteration of copy number, methylation and expression, allowing us to identify cancer-related genes and essential functional modules in cancer. Results We built the Integrated Co-alteration network (ICan) based on multi-omics data, and analyzed the network to uncover cancer-related genes. After comparison with random networks, we identified 155 ovarian cancer-related genes, including well-known (TP53, BRCA1, RB1 and PTEN) and also novel cancer-related genes, such as PDPN and EphA2. We compared the results with a conventional method: CNAmet, and obtained a significantly better area under the curve value (ICan: 0.8179, CNAmet: 0.5183). Conclusion In this paper, we describe a framework to find cancer-related genes based on an Integrated Co-alteration network. Our results proved that ICan could precisely identify candidate cancer genes and provide increased mechanistic understanding of carcinogenesis. This work suggested a new research direction for biological network analyses involving multi-omics data. PMID:25803614

Evaluation of reference genes for reverse transcription quantitative real-time PCR (RT-qPCR) studies in Silene vulgaris considering the method of cDNA preparation

PubMed Central

Koloušková, Pavla; Stone, James D.

2017-01-01

Accurate gene expression measurements are essential in studies of both crop and wild plants. Reverse transcription quantitative real-time PCR (RT-qPCR) has become a preferred tool for gene expression estimation. A selection of suitable reference genes for the normalization of transcript levels is an essential prerequisite of accurate RT-qPCR results. We evaluated the expression stability of eight candidate reference genes across roots, leaves, flower buds and pollen of Silene vulgaris (bladder campion), a model plant for the study of gynodioecy. As random priming of cDNA is recommended for the study of organellar transcripts and poly(A) selection is indicated for nuclear transcripts, we estimated gene expression with both random-primed and oligo(dT)-primed cDNA. Accordingly, we determined reference genes that perform well with oligo(dT)- and random-primed cDNA, making it possible to estimate levels of nucleus-derived transcripts in the same cDNA samples as used for organellar transcripts, a key benefit in studies of cyto-nuclear interactions. Gene expression variance was estimated by RefFinder, which integrates four different analytical tools. The SvACT and SvGAPDH genes were the most stable candidates across various organs of S. vulgaris, regardless of whether pollen was included or not. PMID:28817728

LGscore: A method to identify disease-related genes using biological literature and Google data.

PubMed

Kim, Jeongwoo; Kim, Hyunjin; Yoon, Youngmi; Park, Sanghyun

2015-04-01

Since the genome project in 1990s, a number of studies associated with genes have been conducted and researchers have confirmed that genes are involved in disease. For this reason, the identification of the relationships between diseases and genes is important in biology. We propose a method called LGscore, which identifies disease-related genes using Google data and literature data. To implement this method, first, we construct a disease-related gene network using text-mining results. We then extract gene-gene interactions based on co-occurrences in abstract data obtained from PubMed, and calculate the weights of edges in the gene network by means of Z-scoring. The weights contain two values: the frequency and the Google search results. The frequency value is extracted from literature data, and the Google search result is obtained using Google. We assign a score to each gene through a network analysis. We assume that genes with a large number of links and numerous Google search results and frequency values are more likely to be involved in disease. For validation, we investigated the top 20 inferred genes for five different diseases using answer sets. The answer sets comprised six databases that contain information on disease-gene relationships. We identified a significant number of disease-related genes as well as candidate genes for Alzheimer's disease, diabetes, colon cancer, lung cancer, and prostate cancer. Our method was up to 40% more accurate than existing methods. Copyright © 2015 Elsevier Inc. All rights reserved.

Schizophrenia, vitamin D, and brain development.

PubMed

Mackay-Sim, Alan; Féron, François; Eyles, Darryl; Burne, Thomas; McGrath, John

2004-01-01

Schizophrenia research is invigorated at present by the recent discovery of several plausible candidate susceptibility genes identified from genetic linkage and gene expression studies of brains from persons with schizophrenia. It is a current challenge to reconcile this gathering evidence for specific candidate susceptibility genes with the "neurodevelopmental hypothesis," which posits that schizophrenia arises from gene-environment interactions that disrupt brain development. We make the case here that schizophrenia may result not from numerous genes of small effect, but a few genes of transcriptional regulation acting during brain development. In particular we propose that low vitamin D during brain development interacts with susceptibility genes to alter the trajectory of brain development, probably by epigenetic regulation that alters gene expression throughout adult life. Vitamin D is an attractive "environmental" candidate because it appears to explain several key epidemiological features of schizophrenia. Vitamin D is an attractive "genetic" candidate because its nuclear hormone receptor regulates gene expression and nervous system development. The polygenic quality of schizophrenia, with linkage to many genes of small effect, maybe brought together via this "vitamin D hypothesis." We also discuss the possibility of a broader set of environmental and genetic factors interacting via the nuclear hormone receptors to affect the development of the brain leading to schizophrenia.

Multi-Dimensional Prioritization of Dental Caries Candidate Genes and Its Enriched Dense Network Modules

PubMed Central

Wang, Quan; Jia, Peilin; Cuenco, Karen T.; Feingold, Eleanor; Marazita, Mary L.; Wang, Lily; Zhao, Zhongming

2013-01-01

A number of genetic studies have suggested numerous susceptibility genes for dental caries over the past decade with few definite conclusions. The rapid accumulation of relevant information, along with the complex architecture of the disease, provides a challenging but also unique opportunity to review and integrate the heterogeneous data for follow-up validation and exploration. In this study, we collected and curated candidate genes from four major categories: association studies, linkage scans, gene expression analyses, and literature mining. Candidate genes were prioritized according to the magnitude of evidence related to dental caries. We then searched for dense modules enriched with the prioritized candidate genes through their protein-protein interactions (PPIs). We identified 23 modules comprising of 53 genes. Functional analyses of these 53 genes revealed three major clusters: cytokine network relevant genes, matrix metalloproteinases (MMPs) family, and transforming growth factor-beta (TGF-β) family, all of which have been previously implicated to play important roles in tooth development and carious lesions. Through our extensive data collection and an integrative application of gene prioritization and PPI network analyses, we built a dental caries-specific sub-network for the first time. Our study provided insights into the molecular mechanisms underlying dental caries. The framework we proposed in this work can be applied to other complex diseases. PMID:24146904

Integrative Approach to Pain Genetics Identifies Pain Sensitivity Loci across Diseases

PubMed Central

Ruau, David; Dudley, Joel T.; Chen, Rong; Phillips, Nicholas G.; Swan, Gary E.; Lazzeroni, Laura C.; Clark, J. David

2012-01-01

Identifying human genes relevant for the processing of pain requires difficult-to-conduct and expensive large-scale clinical trials. Here, we examine a novel integrative paradigm for data-driven discovery of pain gene candidates, taking advantage of the vast amount of existing disease-related clinical literature and gene expression microarray data stored in large international repositories. First, thousands of diseases were ranked according to a disease-specific pain index (DSPI), derived from Medical Subject Heading (MESH) annotations in MEDLINE. Second, gene expression profiles of 121 of these human diseases were obtained from public sources. Third, genes with expression variation significantly correlated with DSPI across diseases were selected as candidate pain genes. Finally, selected candidate pain genes were genotyped in an independent human cohort and prospectively evaluated for significant association between variants and measures of pain sensitivity. The strongest signal was with rs4512126 (5q32, ABLIM3, P = 1.3×10−10) for the sensitivity to cold pressor pain in males, but not in females. Significant associations were also observed with rs12548828, rs7826700 and rs1075791 on 8q22.2 within NCALD (P = 1.7×10−4, 1.8×10−4, and 2.2×10−4 respectively). Our results demonstrate the utility of a novel paradigm that integrates publicly available disease-specific gene expression data with clinical data curated from MEDLINE to facilitate the discovery of pain-relevant genes. This data-derived list of pain gene candidates enables additional focused and efficient biological studies validating additional candidates. PMID:22685391

Genome-wide association studies and epistasis analyses of candidate genes related to age at menarche and age at natural menopause in a Korean population.

PubMed

Pyun, Jung-A; Kim, Sunshin; Cho, Nam H; Koh, InSong; Lee, Jong-Young; Shin, Chol; Kwack, KyuBum

2014-05-01

The aim of this study was to identify polymorphisms and gene-gene interactions that are significantly associated with age at menarche and age at menopause in a Korean population. A total of 3,452 and 1,827 women participated in studies of age at menarche and age at natural menopause, respectively. Linear regression analyses adjusted for residence area were used to perform genome-wide association studies (GWAS), candidate gene association studies, and interactions between the candidate genes for age at menarche and age at natural menopause. In GWAS, four single nucleotide polymorphisms (SNPs; rs7528241, rs1324329, rs11597068, and rs6495785) were strongly associated with age at natural menopause (lowest P = 9.66 × 10). However, GWAS of age at menarche did not reveal any strong associations. In candidate gene association studies, SNPs with P < 0.01 were selected to test their synergistic interactions. For age at natural menopause, there was a significant interaction between intronic SNPs on ADAM metallopeptidase with thrombospondin type I motif 9 (ADAMTS9) and SMAD family member 3 (SMAD3) genes (P = 9.52 × 10). For age at menarche, there were three significant interactions between three intronic SNPs on follicle-stimulating hormone receptor (FSHR) gene and one SNP located at the 3' flanking region of insulin-like growth factor 2 receptor (IGF2R) gene (lowest P = 1.95 × 10). Novel SNPs and synergistic interactions between candidate genes are significantly associated with age at menarche and age at natural menopause in a Korean population.

Detecting Coevolution in Mammalian Sperm–Egg Fusion Proteins

PubMed Central

CLAW, KATRINA G.; GEORGE, RENEE D.; SWANSON, WILLIE J.

2018-01-01

SUMMARY Interactions between sperm and egg proteins can occur physically between gamete surface-binding proteins, and genetically between gamete proteins that work in complementary pathways in which they may not physically interact. Physically interacting sperm–egg proteins have been functionally identified in only a few species, and none have been verified within mammals. Candidate genes on both the sperm and egg surfaces exist, but gene deletion studies do not support functional interactions between these sperm–egg proteins; interacting sperm–egg proteins thus remain elusive. Cooperative gamete proteins undergo rapid evolution, and it is predicted that these sperm–egg proteins will also have correlated evolutionary rates due to compensatory changes on both the sperm and egg. To explore potential physical and genetic interactions in sperm–egg proteins, we sequenced four candidate genes from diverse primate species, and used regression and likelihood methods to test for signatures of coevolution between sperm–egg gene pairs. With both methods, we found that the egg protein CD9 coevolves with the sperm protein IZUMO1, suggesting a physical or genetic interaction occurs between them. With regression analysis, we found that CD9 and CRISP2 have correlated rates of evolution, and with likelihood analysis, that CD9 and CRISP1 have correlated rates. This suggests that the different tests may reflect different levels of interaction, be it physical or genetic. Coevolution tests thus provide an exploratory method for detecting potentially interacting sperm–egg protein pairs. PMID:24644026

Detecting coevolution in mammalian sperm-egg fusion proteins.

PubMed

Claw, Katrina G; George, Renee D; Swanson, Willie J

2014-06-01

Interactions between sperm and egg proteins can occur physically between gamete surface-binding proteins, and genetically between gamete proteins that work in complementary pathways in which they may not physically interact. Physically interacting sperm-egg proteins have been functionally identified in only a few species, and none have been verified within mammals. Candidate genes on both the sperm and egg surfaces exist, but gene deletion studies do not support functional interactions between these sperm-egg proteins; interacting sperm-egg proteins thus remain elusive. Cooperative gamete proteins undergo rapid evolution, and it is predicted that these sperm-egg proteins will also have correlated evolutionary rates due to compensatory changes on both the sperm and egg. To explore potential physical and genetic interactions in sperm-egg proteins, we sequenced four candidate genes from diverse primate species, and used regression and likelihood methods to test for signatures of coevolution between sperm-egg gene pairs. With both methods, we found that the egg protein CD9 coevolves with the sperm protein IZUMO1, suggesting a physical or genetic interaction occurs between them. With regression analysis, we found that CD9 and CRISP2 have correlated rates of evolution, and with likelihood analysis, that CD9 and CRISP1 have correlated rates. This suggests that the different tests may reflect different levels of interaction, be it physical or genetic. Coevolution tests thus provide an exploratory method for detecting potentially interacting sperm-egg protein pairs. © 2014 Wiley Periodicals, Inc.

An efficient method for native protein purification in the selected range from prostate cancer tissue digests

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ahmad, Rumana; Nicora, Carrie D.; Shukla, Anil K.

Prostate cancer (CP) cells differ from their normal counterpart in gene expression. Genes encoding secreted or extracellular proteins with increased expression in CP may serve as potential biomarkers. For their detection and quantification, assays based on monoclonal antibodies are best suited for development in a clinical setting. One approach to obtain antibodies is to use recombinant proteins as immunogen. However, the synthesis of recombinant protein for each identified candidate is time-consuming and expensive. It is also not practical to generate high quality antibodies to all identified candidates individually. Furthermore, non-native forms (e.g., recombinant) of proteins may not always lead tomore » useful antibodies. Our approach was to purify a subset of proteins from CP tissue specimens for use as immunogen.« less

Evaluation of RNA from human trabecular bone and identification of stable reference genes.

PubMed

Cepollaro, Simona; Della Bella, Elena; de Biase, Dario; Visani, Michela; Fini, Milena

2018-06-01

The isolation of good quality RNA from tissues is an essential prerequisite for gene expression analysis to study pathophysiological processes. This study evaluated the RNA isolated from human trabecular bone and defined a set of stable reference genes. After pulverization, RNA was extracted with a phenol/chloroform method and then purified using silica columns. The A260/280 ratio, A260/230 ratio, RIN, and ribosomal ratio were measured to evaluate RNA quality and integrity. Moreover, the expression of six candidates was analyzed by qPCR and different algorithms were applied to assess reference gene stability. A good purity and quality of RNA was achieved according to A260/280 and A260/230 ratios, and RIN values. TBP, YWHAZ, and PGK1 were the most stable reference genes that should be used for gene expression analysis. In summary, the method proposed is suitable for gene expression evaluation in human bone and a set of reliable reference genes has been identified. © 2017 Wiley Periodicals, Inc.

Characterization of the human RAB38 and RAB7 genes: exclusion of new major pathological loci for Japanese OCA.

PubMed

Suzuki, Tamio; Miyamura, Yoshinori; Inagaki, Katsuhiko; Tomita, Yasushi

2003-08-01

Oculocutaneous albinisms (OCAs) are due to various gene mutations that cause a disruption of melanogenesis in the melanocyte. Four different genes associated with human OCA have been reported, however, not all of OCA patients can be classified according to these four genes. We have sought to find a new major locus for Japanese OCA. Recently two genes, RAB38 and RAB7, were reported to play an important role in melanogenesis in the melanocyte, suggesting that these two genes could be good candidates for new OCA loci. To determine the structures of the human RAB38 and RAB7 genes, and examine if the two genes are new major loci for Japanese OCA. We screened mutations in these genes of 25 Japanese OCA patients who lacked mutations in the OCA1 and OCA2 genes with SSCP/heteroduplexes method. We determined the both genes, and their genomic organizations to design the primers for SSCP/heteroduplexes method. And then we screened mutations, but no mutation was detected. Neither of the genes is a new major locus for Japanese OCA.

Chapter 15: Disease Gene Prioritization

PubMed Central

Bromberg, Yana

2013-01-01

Disease-causing aberrations in the normal function of a gene define that gene as a disease gene. Proving a causal link between a gene and a disease experimentally is expensive and time-consuming. Comprehensive prioritization of candidate genes prior to experimental testing drastically reduces the associated costs. Computational gene prioritization is based on various pieces of correlative evidence that associate each gene with the given disease and suggest possible causal links. A fair amount of this evidence comes from high-throughput experimentation. Thus, well-developed methods are necessary to reliably deal with the quantity of information at hand. Existing gene prioritization techniques already significantly improve the outcomes of targeted experimental studies. Faster and more reliable techniques that account for novel data types are necessary for the development of new diagnostics, treatments, and cure for many diseases. PMID:23633938

Finding gene regulatory network candidates using the gene expression knowledge base.

PubMed

Venkatesan, Aravind; Tripathi, Sushil; Sanz de Galdeano, Alejandro; Blondé, Ward; Lægreid, Astrid; Mironov, Vladimir; Kuiper, Martin

2014-12-10

Network-based approaches for the analysis of large-scale genomics data have become well established. Biological networks provide a knowledge scaffold against which the patterns and dynamics of 'omics' data can be interpreted. The background information required for the construction of such networks is often dispersed across a multitude of knowledge bases in a variety of formats. The seamless integration of this information is one of the main challenges in bioinformatics. The Semantic Web offers powerful technologies for the assembly of integrated knowledge bases that are computationally comprehensible, thereby providing a potentially powerful resource for constructing biological networks and network-based analysis. We have developed the Gene eXpression Knowledge Base (GeXKB), a semantic web technology based resource that contains integrated knowledge about gene expression regulation. To affirm the utility of GeXKB we demonstrate how this resource can be exploited for the identification of candidate regulatory network proteins. We present four use cases that were designed from a biological perspective in order to find candidate members relevant for the gastrin hormone signaling network model. We show how a combination of specific query definitions and additional selection criteria derived from gene expression data and prior knowledge concerning candidate proteins can be used to retrieve a set of proteins that constitute valid candidates for regulatory network extensions. Semantic web technologies provide the means for processing and integrating various heterogeneous information sources. The GeXKB offers biologists such an integrated knowledge resource, allowing them to address complex biological questions pertaining to gene expression. This work illustrates how GeXKB can be used in combination with gene expression results and literature information to identify new potential candidates that may be considered for extending a gene regulatory network.

The effects of polymorphisms in IL-2, IFN-γ, TGF-β2, IgL, TLR-4, MD-2, and iNOS genes on resistance to Salmonella enteritidis in indigenous chickens.

PubMed

Tohidi, Reza; Idris, Ismail Bin; Panandam, Jothi Malar; Bejo, Mohd Hair

2012-12-01

Salmonella Enteritidis is a major cause of food poisoning worldwide, and poultry products are the main source of S. Enteritidis contamination for humans. Among the numerous strategies for disease control, improving genetic resistance to S. Enteritidis has been the most effective approach. We investigated the association between S. Enteritidis burden in the caecum, spleen, and liver of young indigenous chickens and seven candidate genes, selected on the basis of their critical roles in immunological functions. The genes included those encoding interleukin 2 (IL-2), interferon-γ (IFN-γ), transforming growth factor β2 (TGF-β2), immunoglobulin light chain (IgL), toll-like receptor 4 (TLR-4), myeloid differentiation protein 2 (MD-2), and inducible nitric oxide synthase (iNOS). Two Malaysian indigenous chicken breeds were used as sustainable genetic sources of alleles that are resistant to salmonellosis. The polymerase chain reaction restriction fragment-length polymorphism technique was used to genotype the candidate genes. Three different genotypes were observed in all of the candidate genes, except for MD-2. All of the candidate genes showed the Hardy-Weinberg equilibrium for the two populations. The IL-2-MnlI polymorphism was associated with S. Enteritidis burden in the caecum and spleen. The TGF-β2-RsaI, TLR-4-Sau 96I, and iNOS-AluI polymorphisms were associated with the caecum S. Enteritidis load. The other candidate genes were not associated with S. Enteritidis load in any organ. The results indicate that the IL-2, TGF-β2, TLR-4, and iNOS genes are potential candidates for use in selection programmes for increasing genetic resistance against S. Enteritidis in Malaysian indigenous chickens.

Biomarker Identification for Prostate Cancer and Lymph Node Metastasis from Microarray Data and Protein Interaction Network Using Gene Prioritization Method

PubMed Central

Arias, Carlos Roberto; Yeh, Hsiang-Yuan; Soo, Von-Wun

2012-01-01

Finding a genetic disease-related gene is not a trivial task. Therefore, computational methods are needed to present clues to the biomedical community to explore genes that are more likely to be related to a specific disease as biomarker. We present biomarker identification problem using gene prioritization method called gene prioritization from microarray data based on shortest paths, extended with structural and biological properties and edge flux using voting scheme (GP-MIDAS-VXEF). The method is based on finding relevant interactions on protein interaction networks, then scoring the genes using shortest paths and topological analysis, integrating the results using a voting scheme and a biological boosting. We applied two experiments, one is prostate primary and normal samples and the other is prostate primary tumor with and without lymph nodes metastasis. We used 137 truly prostate cancer genes as benchmark. In the first experiment, GP-MIDAS-VXEF outperforms all the other state-of-the-art methods in the benchmark by retrieving the truest related genes from the candidate set in the top 50 scores found. We applied the same technique to infer the significant biomarkers in prostate cancer with lymph nodes metastasis which is not established well. PMID:22654636

Case-Control Study of Candidate Gene Methylation and Adenomatous Polyp Formation

PubMed Central

M, Alexander; JB, Burch; SE, Steck; C-F, Chen; TG, Hurley; P, Cavicchia; N, Shivappa; J, Guess; H, Zhang; SD, Youngstedt; KE, Creek; S, Lloyd; K, Jones; JR, Hébert

2016-01-01

Purpose Colorectal cancer (CRC) is one of the most common and preventable forms of cancer, but remains the second leading cause of cancer-related death. Colorectal adenomas are precursor lesions that develop in 70–90% of CRC cases. Identification of peripheral biomarkers for adenomas would help to enhance screening efforts. This exploratory study examined the methylation status of 20 candidate markers in peripheral blood leukocytes and their association with adenoma formation. Methods Patients recruited from a local endoscopy clinic provided informed consent, and completed an interview to ascertain demographic, lifestyle, and adenoma risk factors. Cases were individuals with a histopathologically confirmed adenoma, and controls included patients with a normal colonoscopy, or those with histopathological findings not requiring heightened surveillance (normal biopsy, hyperplastic polyp). Methylation-specific polymerase chain reaction was used to characterize candidate gene promoter methylation. Odds ratios and 95% confidence intervals (OR, 95% CI) were calculated using unconditional multivariable logistic regression to test the hypothesis that candidate gene methylation differed between cases and controls, after adjustment for confounders. Results Complete data were available for 107 participants; 36% had adenomas (men: 40%, women: 31%). Hypomethylation of the MINT1 locus (OR: 5.3, 95% CI: 1.0–28.2), and the PER1 (OR: 2.9, 95% CI: 1.1–7.7) and PER3 (OR: 11.6, 95% CI: 1.6–78.5) clock gene promoters was more common among adenoma cases. While specificity was moderate to high for the three markers (71–97%), sensitivity was relatively low (18–45%). Conclusion Follow-up of these epigenetic markers is suggested to further evaluate their utility for adenoma screening or surveillance. PMID:27771773

Secretome Characterization and Correlation Analysis Reveal Putative Pathogenicity Mechanisms and Identify Candidate Avirulence Genes in the Wheat Stripe Rust Fungus Puccinia striiformis f. sp. tritici.

PubMed

Xia, Chongjing; Wang, Meinan; Cornejo, Omar E; Jiwan, Derick A; See, Deven R; Chen, Xianming

2017-01-01

Stripe (yellow) rust, caused by Puccinia striiformis f. sp. tritici ( Pst ), is one of the most destructive diseases of wheat worldwide. Planting resistant cultivars is an effective way to control this disease, but race-specific resistance can be overcome quickly due to the rapid evolving Pst population. Studying the pathogenicity mechanisms is critical for understanding how Pst virulence changes and how to develop wheat cultivars with durable resistance to stripe rust. We re-sequenced 7 Pst isolates and included additional 7 previously sequenced isolates to represent balanced virulence/avirulence profiles for several avirulence loci in seretome analyses. We observed an uneven distribution of heterozygosity among the isolates. Secretome comparison of Pst with other rust fungi identified a large portion of species-specific secreted proteins, suggesting that they may have specific roles when interacting with the wheat host. Thirty-two effectors of Pst were identified from its secretome. We identified candidates for Avr genes corresponding to six Yr genes by correlating polymorphisms for effector genes to the virulence/avirulence profiles of the 14 Pst isolates. The putative AvYr76 was present in the avirulent isolates, but absent in the virulent isolates, suggesting that deleting the coding region of the candidate avirulence gene has produced races virulent to resistance gene Yr76 . We conclude that incorporating avirulence/virulence phenotypes into correlation analysis with variations in genomic structure and secretome, particularly presence/absence polymorphisms of effectors, is an efficient way to identify candidate Avr genes in Pst . The candidate effector genes provide a rich resource for further studies to determine the evolutionary history of Pst populations and the co-evolutionary arms race between Pst and wheat. The Avr candidates identified in this study will lead to cloning avirulence genes in Pst , which will enable us to understand molecular mechanisms underlying Pst -wheat interactions, to determine the effectiveness of resistance genes and further to develop durable resistance to stripe rust.

Selection and Evaluation of Potential Reference Genes for Gene Expression Analysis in the Brown Planthopper, Nilaparvata lugens (Hemiptera: Delphacidae) Using Reverse-Transcription Quantitative PCR

PubMed Central

Zhu, Xun; Wan, Hu; Shakeel, Muhammad; Zhan, Sha; Jin, Byung-Rae; Li, Jianhong

2014-01-01

The brown planthopper (BPH), Nilaparvata lugens (Hemiptera, Delphacidae), is one of the most important rice pests. Abundant genetic studies on BPH have been conducted using reverse-transcription quantitative real-time PCR (qRT-PCR). Using qRT-PCR, the expression levels of target genes are calculated on the basis of endogenous controls. These genes need to be appropriately selected by experimentally assessing whether they are stably expressed under different conditions. However, such studies on potential reference genes in N. lugens are lacking. In this paper, we presented a systematic exploration of eight candidate reference genes in N. lugens, namely, actin 1 (ACT), muscle actin (MACT), ribosomal protein S11 (RPS11), ribosomal protein S15e (RPS15), alpha 2-tubulin (TUB), elongation factor 1 delta (EF), 18S ribosomal RNA (18S), and arginine kinase (AK) and used four alternative methods (BestKeeper, geNorm, NormFinder, and the delta Ct method) to evaluate the suitability of these genes as endogenous controls. We examined their expression levels among different experimental factors (developmental stage, body part, geographic population, temperature variation, pesticide exposure, diet change, and starvation) following the MIQE (Minimum Information for publication of Quantitative real time PCR Experiments) guidelines. Based on the results of RefFinder, which integrates four currently available major software programs to compare and rank the tested candidate reference genes, RPS15, RPS11, and TUB were found to be the most suitable reference genes in different developmental stages, body parts, and geographic populations, respectively. RPS15 was the most suitable gene under different temperature and diet conditions, while RPS11 was the most suitable gene under different pesticide exposure and starvation conditions. This work sheds light on establishing a standardized qRT-PCR procedure in N. lugens, and serves as a starting point for screening for reference genes for expression studies of related insects. PMID:24466124

Selection and evaluation of potential reference genes for gene expression analysis in the brown planthopper, Nilaparvata lugens (Hemiptera: Delphacidae) using reverse-transcription quantitative PCR.

PubMed

Yuan, Miao; Lu, Yanhui; Zhu, Xun; Wan, Hu; Shakeel, Muhammad; Zhan, Sha; Jin, Byung-Rae; Li, Jianhong

2014-01-01

The brown planthopper (BPH), Nilaparvata lugens (Hemiptera, Delphacidae), is one of the most important rice pests. Abundant genetic studies on BPH have been conducted using reverse-transcription quantitative real-time PCR (qRT-PCR). Using qRT-PCR, the expression levels of target genes are calculated on the basis of endogenous controls. These genes need to be appropriately selected by experimentally assessing whether they are stably expressed under different conditions. However, such studies on potential reference genes in N. lugens are lacking. In this paper, we presented a systematic exploration of eight candidate reference genes in N. lugens, namely, actin 1 (ACT), muscle actin (MACT), ribosomal protein S11 (RPS11), ribosomal protein S15e (RPS15), alpha 2-tubulin (TUB), elongation factor 1 delta (EF), 18S ribosomal RNA (18S), and arginine kinase (AK) and used four alternative methods (BestKeeper, geNorm, NormFinder, and the delta Ct method) to evaluate the suitability of these genes as endogenous controls. We examined their expression levels among different experimental factors (developmental stage, body part, geographic population, temperature variation, pesticide exposure, diet change, and starvation) following the MIQE (Minimum Information for publication of Quantitative real time PCR Experiments) guidelines. Based on the results of RefFinder, which integrates four currently available major software programs to compare and rank the tested candidate reference genes, RPS15, RPS11, and TUB were found to be the most suitable reference genes in different developmental stages, body parts, and geographic populations, respectively. RPS15 was the most suitable gene under different temperature and diet conditions, while RPS11 was the most suitable gene under different pesticide exposure and starvation conditions. This work sheds light on establishing a standardized qRT-PCR procedure in N. lugens, and serves as a starting point for screening for reference genes for expression studies of related insects.

Array-based comparative genomic hybridization-guided identification of reference genes for normalization of real-time quantitative polymerase chain reaction assay data for lymphomas, histiocytic sarcomas, and osteosarcomas of dogs.

PubMed

Tsai, Pei-Chien; Breen, Matthew

2012-09-01

To identify suitable reference genes for normalization of real-time quantitative PCR (RT-qPCR) assay data for common tumors of dogs. Malignant lymph node (n = 8), appendicular osteosarcoma (9), and histiocytic sarcoma (12) samples and control samples of various nonneoplastic canine tissues. Array-based comparative genomic hybridization (aCGH) data were used to guide selection of 9 candidate reference genes. Expression stability of candidate reference genes and 4 commonly used reference genes was determined for tumor samples with RT-qPCR assays and 3 software programs. LOC611555 was the candidate reference gene with the highest expression stability among the 3 tumor types. Of the commonly used reference genes, expression stability of HPRT was high in histiocytic sarcoma samples, and expression stability of Ubi and RPL32 was high in osteosarcoma samples. Some of the candidate reference genes had higher expression stability than did the commonly used reference genes. Data for constitutively expressed genes with high expression stability are required for normalization of RT-qPCR assay results. Without such data, accurate quantification of gene expression in tumor tissue samples is difficult. Results of the present study indicated LOC611555 may be a useful RT-qPCR assay reference gene for multiple tissue types. Some commonly used reference genes may be suitable for normalization of gene expression data for tumors of dogs, such as lymphomas, osteosarcomas, or histiocytic sarcomas.

A specific endogenous reference for genetically modified common bean (Phaseolus vulgaris L.) DNA quantification by real-time PCR targeting lectin gene.

PubMed

Venturelli, Gustavo L; Brod, Fábio C A; Rossi, Gabriela B; Zimmermann, Naíra F; Oliveira, Jaison P; Faria, Josias C; Arisi, Ana C M

2014-11-01

The Embrapa 5.1 genetically modified (GM) common bean was approved for commercialization in Brazil. Methods for the quantification of this new genetically modified organism (GMO) are necessary. The development of a suitable endogenous reference is essential for GMO quantification by real-time PCR. Based on this, a new taxon-specific endogenous reference quantification assay was developed for Phaseolus vulgaris L. Three genes encoding common bean proteins (phaseolin, arcelin, and lectin) were selected as candidates for endogenous reference. Primers targeting these candidate genes were designed and the detection was evaluated using the SYBR Green chemistry. The assay targeting lectin gene showed higher specificity than the remaining assays, and a hydrolysis probe was then designed. This assay showed high specificity for 50 common bean samples from two gene pools, Andean and Mesoamerican. For GM common bean varieties, the results were similar to those obtained for non-GM isogenic varieties with PCR efficiency values ranging from 92 to 101 %. Moreover, this assay presented a limit of detection of ten haploid genome copies. The primers and probe developed in this work are suitable to detect and quantify either GM or non-GM common bean.

Genome-wide association links candidate genes to resistance to Plum Pox Virus in apricot (Prunus armeniaca).

PubMed

Mariette, Stéphanie; Wong Jun Tai, Fabienne; Roch, Guillaume; Barre, Aurélien; Chague, Aurélie; Decroocq, Stéphane; Groppi, Alexis; Laizet, Yec'han; Lambert, Patrick; Tricon, David; Nikolski, Macha; Audergon, Jean-Marc; Abbott, Albert G; Decroocq, Véronique

2016-01-01

In fruit tree species, many important traits have been characterized genetically by using single-family descent mapping in progenies segregating for the traits. However, most mapped loci have not been sufficiently resolved to the individual genes due to insufficient progeny sizes for high resolution mapping and the previous lack of whole-genome sequence resources of the study species. To address this problem for Plum Pox Virus (PPV) candidate resistance gene identification in Prunus species, we implemented a genome-wide association (GWA) approach in apricot. This study exploited the broad genetic diversity of the apricot (Prunus armeniaca) germplasm containing resistance to PPV, next-generation sequence-based genotyping, and the high-quality peach (Prunus persica) genome reference sequence for single nucleotide polymorphism (SNP) identification. The results of this GWA study validated previously reported PPV resistance quantitative trait loci (QTL) intervals, highlighted other potential resistance loci, and resolved each to a limited set of candidate genes for further study. This work substantiates the association genetics approach for resolution of QTL to candidate genes in apricot and suggests that this approach could simplify identification of other candidate genes for other marked trait intervals in this germplasm. © 2015 INRA, UMR 1332 BFP New Phytologist © 2015 New Phytologist Trust.

Candidate genes for idiopathic epilepsy in four dog breeds.

PubMed

Ekenstedt, Kari J; Patterson, Edward E; Minor, Katie M; Mickelson, James R

2011-04-25

Idiopathic epilepsy (IE) is a naturally occurring and significant seizure disorder affecting all dog breeds. Because dog breeds are genetically isolated populations, it is possible that IE is attributable to common founders and is genetically homogenous within breeds. In humans, a number of mutations, the majority of which are genes encoding ion channels, neurotransmitters, or their regulatory subunits, have been discovered to cause rare, specific types of IE. It was hypothesized that there are simple genetic bases for IE in some purebred dog breeds, specifically in Vizslas, English Springer Spaniels (ESS), Greater Swiss Mountain Dogs (GSMD), and Beagles, and that the gene(s) responsible may, in some cases, be the same as those already discovered in humans. Candidate genes known to be involved in human epilepsy, along with selected additional genes in the same gene families that are involved in murine epilepsy or are expressed in neural tissue, were examined in populations of affected and unaffected dogs. Microsatellite markers in close proximity to each candidate gene were genotyped and subjected to two-point linkage in Vizslas, and association analysis in ESS, GSMD and Beagles. Most of these candidate genes were not significantly associated with IE in these four dog breeds, while a few genes remained inconclusive. Other genes not included in this study may still be causing monogenic IE in these breeds or, like many cases of human IE, the disease in dogs may be likewise polygenic.

Adaptation to climate through flowering phenology: a case study in Medicago truncatula.

PubMed

Burgarella, Concetta; Chantret, Nathalie; Gay, Laurène; Prosperi, Jean-Marie; Bonhomme, Maxime; Tiffin, Peter; Young, Nevin D; Ronfort, Joelle

2016-07-01

Local climatic conditions likely constitute an important selective pressure on genes underlying important fitness-related traits such as flowering time, and in many species, flowering phenology and climatic gradients strongly covary. To test whether climate shapes the genetic variation on flowering time genes and to identify candidate flowering genes involved in the adaptation to environmental heterogeneity, we used a large Medicago truncatula core collection to examine the association between nucleotide polymorphisms at 224 candidate genes and both climate variables and flowering phenotypes. Unlike genome-wide studies, candidate gene approaches are expected to enrich for the number of meaningful trait associations because they specifically target genes that are known to affect the trait of interest. We found that flowering time mediates adaptation to climatic conditions mainly by variation at genes located upstream in the flowering pathways, close to the environmental stimuli. Variables related to the annual precipitation regime reflected selective constraints on flowering time genes better than the other variables tested (temperature, altitude, latitude or longitude). By comparing phenotype and climate associations, we identified 12 flowering genes as the most promising candidates responsible for phenological adaptation to climate. Four of these genes were located in the known flowering time QTL region on chromosome 7. However, climate and flowering associations also highlighted largely distinct gene sets, suggesting different genetic architectures for adaptation to climate and flowering onset. © 2016 John Wiley & Sons Ltd.

Gene Targeting in Rabbits: Single-Step Generation of Knock-out Rabbits by Microinjection of CRISPR/Cas9 Plasmids.

PubMed

Kawano, Yoshihiro; Honda, Arata

2017-01-01

The development of genome editing technology has allowed gene disruptions to be achieved in various animal species and has been beneficial to many mammals. Gene disruption using pluripotent stem cells is difficult to achieve in rabbits, but thanks to advances in genome editing technology, a number of gene disruptions have been conducted. This paper describes a simple and easy method for carrying out gene disruptions in rabbits using CRISPR/Cas9 in which the gene to be disrupted is marked, the presence or absence of off-target candidates is checked, and a plasmid allowing simultaneous expression of Cas9 and sgRNA is constructed. Next, the cleaving activity of candidate sequences is investigated, and assessments are carried out to determine whether the target sequences can be cut. Female rabbits subjected to superovulation treatment are mated with male rabbits and fertilized eggs are collected, and then pronuclear injection of plasmid DNA is performed. The next day, the two-cell stage embryos are transplanted into pseudopregnant rabbits, and offspring are born within approximately 29-30 days. The genomic DNA of the offspring is then examined to check what types of genetic modifications have occurred. With the advent of CRISPR/Cas9, the accessibility of gene disruptions in rabbits has improved remarkably. This paper summarizes specifically how to carry out gene disruptions in rabbits.

Sporulation genes associated with sporulation efficiency in natural isolates of yeast.

PubMed

Tomar, Parul; Bhatia, Aatish; Ramdas, Shweta; Diao, Liyang; Bhanot, Gyan; Sinha, Himanshu

2013-01-01

Yeast sporulation efficiency is a quantitative trait and is known to vary among experimental populations and natural isolates. Some studies have uncovered the genetic basis of this variation and have identified the role of sporulation genes (IME1, RME1) and sporulation-associated genes (FKH2, PMS1, RAS2, RSF1, SWS2), as well as non-sporulation pathway genes (MKT1, TAO3) in maintaining this variation. However, these studies have been done mostly in experimental populations. Sporulation is a response to nutrient deprivation. Unlike laboratory strains, natural isolates have likely undergone multiple selections for quick adaptation to varying nutrient conditions. As a result, sporulation efficiency in natural isolates may have different genetic factors contributing to phenotypic variation. Using Saccharomyces cerevisiae strains in the genetically and environmentally diverse SGRP collection, we have identified genetic loci associated with sporulation efficiency variation in a set of sporulation and sporulation-associated genes. Using two independent methods for association mapping and correcting for population structure biases, our analysis identified two linked clusters containing 4 non-synonymous mutations in genes - HOS4, MCK1, SET3, and SPO74. Five regulatory polymorphisms in five genes such as MLS1 and CDC10 were also identified as putative candidates. Our results provide candidate genes contributing to phenotypic variation in the sporulation efficiency of natural isolates of yeast.

Sporulation Genes Associated with Sporulation Efficiency in Natural Isolates of Yeast

PubMed Central

Ramdas, Shweta; Diao, Liyang; Bhanot, Gyan; Sinha, Himanshu

2013-01-01

Yeast sporulation efficiency is a quantitative trait and is known to vary among experimental populations and natural isolates. Some studies have uncovered the genetic basis of this variation and have identified the role of sporulation genes (IME1, RME1) and sporulation-associated genes (FKH2, PMS1, RAS2, RSF1, SWS2), as well as non-sporulation pathway genes (MKT1, TAO3) in maintaining this variation. However, these studies have been done mostly in experimental populations. Sporulation is a response to nutrient deprivation. Unlike laboratory strains, natural isolates have likely undergone multiple selections for quick adaptation to varying nutrient conditions. As a result, sporulation efficiency in natural isolates may have different genetic factors contributing to phenotypic variation. Using Saccharomyces cerevisiae strains in the genetically and environmentally diverse SGRP collection, we have identified genetic loci associated with sporulation efficiency variation in a set of sporulation and sporulation-associated genes. Using two independent methods for association mapping and correcting for population structure biases, our analysis identified two linked clusters containing 4 non-synonymous mutations in genes – HOS4, MCK1, SET3, and SPO74. Five regulatory polymorphisms in five genes such as MLS1 and CDC10 were also identified as putative candidates. Our results provide candidate genes contributing to phenotypic variation in the sporulation efficiency of natural isolates of yeast. PMID:23874994

Transcriptome profiling of two maize inbreds with distinct responses to Gibberella ear rot disease to identify candidate resistance genes.

PubMed

Kebede, Aida Z; Johnston, Anne; Schneiderman, Danielle; Bosnich, Whynn; Harris, Linda J

2018-02-09

Gibberella ear rot (GER) is one of the most economically important fungal diseases of maize in the temperate zone due to moldy grain contaminated with health threatening mycotoxins. To develop resistant genotypes and control the disease, understanding the host-pathogen interaction is essential. RNA-Seq-derived transcriptome profiles of fungal- and mock-inoculated developing kernel tissues of two maize inbred lines were used to identify differentially expressed transcripts and propose candidate genes mapping within GER resistance quantitative trait loci (QTL). A total of 1255 transcripts were significantly (P ≤ 0.05) up regulated due to fungal infection in both susceptible and resistant inbreds. A greater number of transcripts were up regulated in the former (1174) than the latter (497) and increased as the infection progressed from 1 to 2 days after inoculation. Focusing on differentially expressed genes located within QTL regions for GER resistance, we identified 81 genes involved in membrane transport, hormone regulation, cell wall modification, cell detoxification, and biosynthesis of pathogenesis related proteins and phytoalexins as candidate genes contributing to resistance. Applying droplet digital PCR, we validated the expression profiles of a subset of these candidate genes from QTL regions contributed by the resistant inbred on chromosomes 1, 2 and 9. By screening global gene expression profiles for differentially expressed genes mapping within resistance QTL regions, we have identified candidate genes for gibberella ear rot resistance on several maize chromosomes which could potentially lead to a better understanding of Fusarium resistance mechanisms.

An Integrative Genetics Approach to Identify Candidate Genes Regulating BMD: Combining Linkage, Gene Expression, and Association

PubMed Central

Farber, Charles R; van Nas, Atila; Ghazalpour, Anatole; Aten, Jason E; Doss, Sudheer; Sos, Brandon; Schadt, Eric E; Ingram-Drake, Leslie; Davis, Richard C; Horvath, Steve; Smith, Desmond J; Drake, Thomas A; Lusis, Aldons J

2009-01-01

Numerous quantitative trait loci (QTLs) affecting bone traits have been identified in the mouse; however, few of the underlying genes have been discovered. To improve the process of transitioning from QTL to gene, we describe an integrative genetics approach, which combines linkage analysis, expression QTL (eQTL) mapping, causality modeling, and genetic association in outbred mice. In C57BL/6J × C3H/HeJ (BXH) F2 mice, nine QTLs regulating femoral BMD were identified. To select candidate genes from within each QTL region, microarray gene expression profiles from individual F2 mice were used to identify 148 genes whose expression was correlated with BMD and regulated by local eQTLs. Many of the genes that were the most highly correlated with BMD have been previously shown to modulate bone mass or skeletal development. Candidates were further prioritized by determining whether their expression was predicted to underlie variation in BMD. Using network edge orienting (NEO), a causality modeling algorithm, 18 of the 148 candidates were predicted to be causally related to differences in BMD. To fine-map QTLs, markers in outbred MF1 mice were tested for association with BMD. Three chromosome 11 SNPs were identified that were associated with BMD within the Bmd11 QTL. Finally, our approach provides strong support for Wnt9a, Rasd1, or both underlying Bmd11. Integration of multiple genetic and genomic data sets can substantially improve the efficiency of QTL fine-mapping and candidate gene identification. PMID:18767929

Allelic-based gene-gene interaction associated with quantitative traits.

PubMed

Jung, Jeesun; Sun, Bin; Kwon, Deukwoo; Koller, Daniel L; Foroud, Tatiana M

2009-05-01

Recent studies have shown that quantitative phenotypes may be influenced not only by multiple single nucleotide polymorphisms (SNPs) within a gene but also by the interaction between SNPs at unlinked genes. We propose a new statistical approach that can detect gene-gene interactions at the allelic level which contribute to the phenotypic variation in a quantitative trait. By testing for the association of allelic combinations at multiple unlinked loci with a quantitative trait, we can detect the SNP allelic interaction whether or not it can be detected as a main effect. Our proposed method assigns a score to unrelated subjects according to their allelic combination inferred from observed genotypes at two or more unlinked SNPs, and then tests for the association of the allelic score with a quantitative trait. To investigate the statistical properties of the proposed method, we performed a simulation study to estimate type I error rates and power and demonstrated that this allelic approach achieves greater power than the more commonly used genotypic approach to test for gene-gene interaction. As an example, the proposed method was applied to data obtained as part of a candidate gene study of sodium retention by the kidney. We found that this method detects an interaction between the calcium-sensing receptor gene (CaSR), the chloride channel gene (CLCNKB) and the Na, K, 2Cl cotransporter gene (CLC12A1) that contributes to variation in diastolic blood pressure.

SFM: A novel sequence-based fusion method for disease genes identification and prioritization.

PubMed

Yousef, Abdulaziz; Moghadam Charkari, Nasrollah

2015-10-21

The identification of disease genes from human genome is of great importance to improve diagnosis and treatment of disease. Several machine learning methods have been introduced to identify disease genes. However, these methods mostly differ in the prior knowledge used to construct the feature vector for each instance (gene), the ways of selecting negative data (non-disease genes) where there is no investigational approach to find them and the classification methods used to make the final decision. In this work, a novel Sequence-based fusion method (SFM) is proposed to identify disease genes. In this regard, unlike existing methods, instead of using a noisy and incomplete prior-knowledge, the amino acid sequence of the proteins which is universal data has been carried out to present the genes (proteins) into four different feature vectors. To select more likely negative data from candidate genes, the intersection set of four negative sets which are generated using distance approach is considered. Then, Decision Tree (C4.5) has been applied as a fusion method to combine the results of four independent state-of the-art predictors based on support vector machine (SVM) algorithm, and to make the final decision. The experimental results of the proposed method have been evaluated by some standard measures. The results indicate the precision, recall and F-measure of 82.6%, 85.6% and 84, respectively. These results confirm the efficiency and validity of the proposed method. Copyright © 2015 Elsevier Ltd. All rights reserved.

PAINT: a promoter analysis and interaction network generation tool for gene regulatory network identification.

PubMed

Vadigepalli, Rajanikanth; Chakravarthula, Praveen; Zak, Daniel E; Schwaber, James S; Gonye, Gregory E

2003-01-01

We have developed a bioinformatics tool named PAINT that automates the promoter analysis of a given set of genes for the presence of transcription factor binding sites. Based on coincidence of regulatory sites, this tool produces an interaction matrix that represents a candidate transcriptional regulatory network. This tool currently consists of (1) a database of promoter sequences of known or predicted genes in the Ensembl annotated mouse genome database, (2) various modules that can retrieve and process the promoter sequences for binding sites of known transcription factors, and (3) modules for visualization and analysis of the resulting set of candidate network connections. This information provides a substantially pruned list of genes and transcription factors that can be examined in detail in further experimental studies on gene regulation. Also, the candidate network can be incorporated into network identification methods in the form of constraints on feasible structures in order to render the algorithms tractable for large-scale systems. The tool can also produce output in various formats suitable for use in external visualization and analysis software. In this manuscript, PAINT is demonstrated in two case studies involving analysis of differentially regulated genes chosen from two microarray data sets. The first set is from a neuroblastoma N1E-115 cell differentiation experiment, and the second set is from neuroblastoma N1E-115 cells at different time intervals following exposure to neuropeptide angiotensin II. PAINT is available for use as an agent in BioSPICE simulation and analysis framework (www.biospice.org), and can also be accessed via a WWW interface at www.dbi.tju.edu/dbi/tools/paint/.

Exome sequencing of oral squamous cell carcinoma in users of Arabian snuff reveals novel candidates for driver genes.

PubMed

Al-Hebshi, Nezar Noor; Li, Shiyong; Nasher, Akram Thabet; El-Setouhy, Maged; Alsanosi, Rashad; Blancato, Jan; Loffredo, Christopher

2016-07-15

The study sought to identify genetic aberrations driving oral squamous cell carcinoma (OSCC) development among users of shammah, an Arabian preparation of smokeless tobacco. Twenty archival OSCC samples, 15 of which with a history of shammah exposure, were whole-exome sequenced at an average depth of 127×. Somatic mutations were identified using a novel, matched controls-independent filtration algorithm. CODEX and Exomedepth coupled with a novel, Database of Genomic Variant-based filter were employed to call somatic gene-copy number variations. Significantly mutated genes were identified with Oncodrive FM and the Youn and Simon's method. Candidate driver genes were nominated based on Gene Set Enrichment Analysis. The observed mutational spectrum was similar to that reported by the TCGA project. In addition to confirming known genes of OSCC (TP53, CDKNA2, CASP8, PIK3CA, HRAS, FAT1, TP63, CCND1 and FADD) the analysis identified several candidate novel driver events including mutations of NOTCH3, CSMD3, CRB1, CLTCL1, OSMR and TRPM2, amplification of the proto-oncogenes FOSL1, RELA, TRAF6, MDM2, FRS2 and BAG1, and deletion of the recently described tumor suppressor SMARCC1. Analysis also revealed significantly altered pathways not previously implicated in OSCC including Oncostatin-M signalling pathway, AP-1 and C-MYB transcription networks and endocytosis. There was a trend for higher number of mutations, amplifications and driver events in samples with history of shammah exposure particularly those that tested EBV positive, suggesting an interaction between tobacco exposure and EBV. The work provides further evidence for the genetic heterogeneity of oral cancer and suggests shammah-associated OSCC is characterized by extensive amplification of oncogenes. © 2016 UICC.

A Stratified Transcriptomics Analysis of Polygenic Fat and Lean Mouse Adipose Tissues Identifies Novel Candidate Obesity Genes

PubMed Central

Morton, Nicholas M.; Nelson, Yvonne B.; Michailidou, Zoi; Di Rollo, Emma M.; Ramage, Lynne; Hadoke, Patrick W. F.; Seckl, Jonathan R.; Bunger, Lutz; Horvat, Simon; Kenyon, Christopher J.; Dunbar, Donald R.

2011-01-01

Background Obesity and metabolic syndrome results from a complex interaction between genetic and environmental factors. In addition to brain-regulated processes, recent genome wide association studies have indicated that genes highly expressed in adipose tissue affect the distribution and function of fat and thus contribute to obesity. Using a stratified transcriptome gene enrichment approach we attempted to identify adipose tissue-specific obesity genes in the unique polygenic Fat (F) mouse strain generated by selective breeding over 60 generations for divergent adiposity from a comparator Lean (L) strain. Results To enrich for adipose tissue obesity genes a ‘snap-shot’ pooled-sample transcriptome comparison of key fat depots and non adipose tissues (muscle, liver, kidney) was performed. Known obesity quantitative trait loci (QTL) information for the model allowed us to further filter genes for increased likelihood of being causal or secondary for obesity. This successfully identified several genes previously linked to obesity (C1qr1, and Np3r) as positional QTL candidate genes elevated specifically in F line adipose tissue. A number of novel obesity candidate genes were also identified (Thbs1, Ppp1r3d, Tmepai, Trp53inp2, Ttc7b, Tuba1a, Fgf13, Fmr) that have inferred roles in fat cell function. Quantitative microarray analysis was then applied to the most phenotypically divergent adipose depot after exaggerating F and L strain differences with chronic high fat feeding which revealed a distinct gene expression profile of line, fat depot and diet-responsive inflammatory, angiogenic and metabolic pathways. Selected candidate genes Npr3 and Thbs1, as well as Gys2, a non-QTL gene that otherwise passed our enrichment criteria were characterised, revealing novel functional effects consistent with a contribution to obesity. Conclusions A focussed candidate gene enrichment strategy in the unique F and L model has identified novel adipose tissue-enriched genes contributing to obesity. PMID:21915269

A stratified transcriptomics analysis of polygenic fat and lean mouse adipose tissues identifies novel candidate obesity genes.

PubMed

Morton, Nicholas M; Nelson, Yvonne B; Michailidou, Zoi; Di Rollo, Emma M; Ramage, Lynne; Hadoke, Patrick W F; Seckl, Jonathan R; Bunger, Lutz; Horvat, Simon; Kenyon, Christopher J; Dunbar, Donald R

2011-01-01

Obesity and metabolic syndrome results from a complex interaction between genetic and environmental factors. In addition to brain-regulated processes, recent genome wide association studies have indicated that genes highly expressed in adipose tissue affect the distribution and function of fat and thus contribute to obesity. Using a stratified transcriptome gene enrichment approach we attempted to identify adipose tissue-specific obesity genes in the unique polygenic Fat (F) mouse strain generated by selective breeding over 60 generations for divergent adiposity from a comparator Lean (L) strain. To enrich for adipose tissue obesity genes a 'snap-shot' pooled-sample transcriptome comparison of key fat depots and non adipose tissues (muscle, liver, kidney) was performed. Known obesity quantitative trait loci (QTL) information for the model allowed us to further filter genes for increased likelihood of being causal or secondary for obesity. This successfully identified several genes previously linked to obesity (C1qr1, and Np3r) as positional QTL candidate genes elevated specifically in F line adipose tissue. A number of novel obesity candidate genes were also identified (Thbs1, Ppp1r3d, Tmepai, Trp53inp2, Ttc7b, Tuba1a, Fgf13, Fmr) that have inferred roles in fat cell function. Quantitative microarray analysis was then applied to the most phenotypically divergent adipose depot after exaggerating F and L strain differences with chronic high fat feeding which revealed a distinct gene expression profile of line, fat depot and diet-responsive inflammatory, angiogenic and metabolic pathways. Selected candidate genes Npr3 and Thbs1, as well as Gys2, a non-QTL gene that otherwise passed our enrichment criteria were characterised, revealing novel functional effects consistent with a contribution to obesity. A focussed candidate gene enrichment strategy in the unique F and L model has identified novel adipose tissue-enriched genes contributing to obesity.

Pivotal role of the muscle-contraction pathway in cryptorchidism and evidence for genomic connections with cardiomyopathy pathways in RASopathies.

PubMed

Cannistraci, Carlo V; Ogorevc, Jernej; Zorc, Minja; Ravasi, Timothy; Dovc, Peter; Kunej, Tanja

2013-02-14

Cryptorchidism is the most frequent congenital disorder in male children; however the genetic causes of cryptorchidism remain poorly investigated. Comparative integratomics combined with systems biology approach was employed to elucidate genetic factors and molecular pathways underlying testis descent. Literature mining was performed to collect genomic loci associated with cryptorchidism in seven mammalian species. Information regarding the collected candidate genes was stored in MySQL relational database. Genomic view of the loci was presented using Flash GViewer web tool (http://gmod.org/wiki/Flashgviewer/). DAVID Bioinformatics Resources 6.7 was used for pathway enrichment analysis. Cytoscape plug-in PiNGO 1.11 was employed for protein-network-based prediction of novel candidate genes. Relevant protein-protein interactions were confirmed and visualized using the STRING database (version 9.0). The developed cryptorchidism gene atlas includes 217 candidate loci (genes, regions involved in chromosomal mutations, and copy number variations) identified at the genomic, transcriptomic, and proteomic level. Human orthologs of the collected candidate loci were presented using a genomic map viewer. The cryptorchidism gene atlas is freely available online: http://www.integratomics-time.com/cryptorchidism/. Pathway analysis suggested the presence of twelve enriched pathways associated with the list of 179 literature-derived candidate genes. Additionally, a list of 43 network-predicted novel candidate genes was significantly associated with four enriched pathways. Joint pathway analysis of the collected and predicted candidate genes revealed the pivotal importance of the muscle-contraction pathway in cryptorchidism and evidence for genomic associations with cardiomyopathy pathways in RASopathies. The developed gene atlas represents an important resource for the scientific community researching genetics of cryptorchidism. The collected data will further facilitate development of novel genetic markers and could be of interest for functional studies in animals and human. The proposed network-based systems biology approach elucidates molecular mechanisms underlying co-presence of cryptorchidism and cardiomyopathy in RASopathies. Such approach could also aid in molecular explanation of co-presence of diverse and apparently unrelated clinical manifestations in other syndromes.

Pharmacogenetic Predictors of Methylphenidate Dose-Response in Attention-Deficit/Hyperactivity Disorder

ERIC Educational Resources Information Center

Froehlich, Tanya E.; Epstein, Jeffery N.; Nick, Todd G.; Melguizo Castro, Maria S.; Stein, Mark A.; Brinkman, William B.; Graham, Amanda J.; Langberg, Joshua M.; Kahn, Robert S.

2011-01-01

Objective: Because of significant individual variability in attention-deficit/hyperactivity disorder (ADHD) medication response, there is increasing interest in identifying genetic predictors of treatment effects. This study examined the role of four catecholamine-related candidate genes in moderating methylphenidate (MPH) dose-response. Method:…

Medical subject heading (MeSH) annotations illuminate maize genetics and evolution

USDA-ARS?s Scientific Manuscript database

In the modern era, high-density marker panels and/or whole-genome sequencing,coupled with advanced phenotyping pipelines and sophisticated statistical methods, have dramatically increased our ability to generate lists of candidate genes or regions that are putatively associated with phenotypes or pr...

Genome-Wide Prediction of the Polymorphic Ser Gene Family in Tetrahymena thermophila Based on Motif Analysis

PubMed Central

Ponsuwanna, Patrath; Kümpornsin, Krittikorn; Chookajorn, Thanat

2014-01-01

Even though antigenic variation is employed among parasitic protozoa for host immune evasion, Tetrahymena thermophila, a free-living ciliate, can also change its surface protein antigens. These cysteine-rich glycosylphosphatidylinositol (GPI)-linked surface proteins are encoded by a family of polymorphic Ser genes. Despite the availability of T. thermophila genome, a comprehensive analysis of the Ser family is limited by its high degree of polymorphism. In order to overcome this problem, a new approach was adopted by searching for Ser candidates with common motif sequences, namely length-specific repetitive cysteine pattern and GPI anchor site. The candidate genes were phylogenetically compared with the previously identified Ser genes and classified into subtypes. Ser candidates were often found to be located as tandem arrays of the same subtypes on several chromosomal scaffolds. Certain Ser candidates located in the same chromosomal arrays were transcriptionally expressed at specific T. thermophila developmental stages. These Ser candidates selected by the motif analysis approach can form the foundation for a systematic identification of the entire Ser gene family, which will contribute to the understanding of their function and the basis of T. thermophila antigenic variation. PMID:25133747

Analysis of Craniocardiac Malformations in Xenopus using Optical Coherence Tomography

PubMed Central

Deniz, Engin; Jonas, Stephan; Hooper, Michael; N. Griffin, John; Choma, Michael A.; Khokha, Mustafa K.

2017-01-01

Birth defects affect 3% of children in the United States. Among the birth defects, congenital heart disease and craniofacial malformations are major causes of mortality and morbidity. Unfortunately, the genetic mechanisms underlying craniocardiac malformations remain largely uncharacterized. To address this, human genomic studies are identifying sequence variations in patients, resulting in numerous candidate genes. However, the molecular mechanisms of pathogenesis for most candidate genes are unknown. Therefore, there is a need for functional analyses in rapid and efficient animal models of human disease. Here, we coupled the frog Xenopus tropicalis with Optical Coherence Tomography (OCT) to create a fast and efficient system for testing craniocardiac candidate genes. OCT can image cross-sections of microscopic structures in vivo at resolutions approaching histology. Here, we identify optimal OCT imaging planes to visualize and quantitate Xenopus heart and facial structures establishing normative data. Next we evaluate known human congenital heart diseases: cardiomyopathy and heterotaxy. Finally, we examine craniofacial defects by a known human teratogen, cyclopamine. We recapitulate human phenotypes readily and quantify the functional and structural defects. Using this approach, we can quickly test human craniocardiac candidate genes for phenocopy as a critical first step towards understanding disease mechanisms of the candidate genes. PMID:28195132

Genome-Wide Analysis Identifies IL-18 and FUCA2 as Novel Genes Associated with Diastolic Function in African Americans with Sickle Cell Disease

PubMed Central

Sysol, Justin R.; Abbasi, Taimur; Patel, Amit R.; Lang, Roberto M.; Gupta, Akash; Garcia, Joe G. N.; Gordeuk, Victor R.; Machado, Roberto F.

2016-01-01

Background Diastolic dysfunction is common in sickle cell disease (SCD), and is associated with an increased risk of mortality. However, the molecular pathogenesis underlying this development is poorly understood. The aim of this study was to identify a gene expression profile that is associated with diastolic function in SCD, potentially elucidating molecular mechanisms behind diastolic dysfunction development. Methods Diastolic function was measured via echocardiography in 65 patients with SCD from two independent study populations. Gene expression microarray data was compared with diastolic function in both study cohorts. Candidate genes that associated in both analyses were tested for validation in a murine SCD model. Lastly, genotyping array data from the replication cohort was used to derive cis-expression quantitative trait loci (cis-eQTLs) and genetic associations within the candidate gene regions. Results Transcriptome data from both patient cohorts implicated 7 genes associated with diastolic function, and mouse SCD myocardial expression validated 3 of these genes. Genetic associations and eQTLs were detected in 2 of the 3 genes, FUCA2 and IL18. Conclusions FUCA2 and IL18 are associated with diastolic function in SCD patients, and may be involved in the pathogenesis of the disease. Genetic polymorphisms within the FUCA2 and IL18 gene regions are also associated with diastolic function in SCD, likely by affecting expression levels of the genes. PMID:27636371

A genome scan for selection signatures comparing farmed Atlantic salmon with two wild populations: Testing colocalization among outlier markers, candidate genes, and quantitative trait loci for production traits.

PubMed

Liu, Lei; Ang, Keng Pee; Elliott, J A K; Kent, Matthew Peter; Lien, Sigbjørn; MacDonald, Danielle; Boulding, Elizabeth Grace

2017-03-01

Comparative genome scans can be used to identify chromosome regions, but not traits, that are putatively under selection. Identification of targeted traits may be more likely in recently domesticated populations under strong artificial selection for increased production. We used a North American Atlantic salmon 6K SNP dataset to locate genome regions of an aquaculture strain (Saint John River) that were highly diverged from that of its putative wild founder population (Tobique River). First, admixed individuals with partial European ancestry were detected using STRUCTURE and removed from the dataset. Outlier loci were then identified as those showing extreme differentiation between the aquaculture population and the founder population. All Arlequin methods identified an overlapping subset of 17 outlier loci, three of which were also identified by BayeScan. Many outlier loci were near candidate genes and some were near published quantitative trait loci (QTLs) for growth, appetite, maturity, or disease resistance. Parallel comparisons using a wild, nonfounder population (Stewiacke River) yielded only one overlapping outlier locus as well as a known maturity QTL. We conclude that genome scans comparing a recently domesticated strain with its wild founder population can facilitate identification of candidate genes for traits known to have been under strong artificial selection.

Transcriptional mechanisms of resistance to anti-PD-1 therapy

PubMed Central

Ascierto, Maria L.; Makohon-Moore, Alvin; Lipson, Evan J.; Taube, Janis M.; McMiller, Tracee L.; Berger, Alan E.; Fan, Jinshui; Kaunitz, Genevieve J.; Cottrell, Tricia R.; Kohutek, Zachary A.; Favorov, Alexander; Makarov, Vladimir; Riaz, Nadeem; Chan, Timothy A.; Cope, Leslie; Hruban, Ralph H.; Pardoll, Drew M.; Taylor, Barry S.; Solit, David B.; Iacobuzio-Donahue, Christine A; Topalian, Suzanne L.

2017-01-01

Purpose To explore factors associated with response and resistance to anti-PD-1 therapy, we analyzed multiple disease sites at autopsy in a patient with widely metastatic melanoma who had a heterogeneous response. Materials and Methods Twenty-six melanoma specimens (four pre-mortem, 22 post-mortem) were subjected to whole-exome sequencing. Candidate immunologic markers and gene expression were assessed in ten cutaneous metastases showing response or progression during therapy. Results The melanoma was driven by biallelic inactivation of NF1. All lesions had highly concordant mutational profiles and copy number alterations, indicating linear clonal evolution. Expression of candidate immunologic markers was similar in responding and progressing lesions. However, progressing cutaneous metastases were associated with over-expression of genes associated with extracellular matrix and neutrophil function. Conclusions Although mutational and immunologic differences have been proposed as the primary determinants of heterogeneous response/resistance to targeted therapies and immunotherapies, respectively, differential lesional gene expression profiles may also dictate anti-PD-1 outcomes. PMID:28193624

Using Association Mapping in Teosinte (Zea Mays ssp Parviglumis) to Investigate the Function of Selection-Candidate Genes

USDA-ARS?s Scientific Manuscript database

Large-scale screens of the maize genome identified 48 genes that show the putative signature of artificial selection during maize domestication or improvement. These selection-candidate genes may act as quantitative trait loci (QTL) that control the phenotypic differences between maize and its proge...

Analysis of X chromosome genomic DNA sequence copy number variation associated with premature ovarian failure (POF)

PubMed Central

Quilter, C.R.; Karcanias, A.C.; Bagga, M.R.; Duncan, S.; Murray, A.; Conway, G.S.; Sargent, C.A.; Affara, N.A.

2013-01-01

BACKGROUND Premature ovarian failure (POF) is a heterogeneous disease defined as amenorrhoea for >6 months before age 40, with an FSH serum level >40 mIU/ml (menopausal levels). While there is a strong genetic association with POF, familial studies have also indicated that idiopathic POF may also be genetically linked. Conventional cytogenetic analyses have identified regions of the X chromosome that are strongly associated with ovarian function, as well as several POF candidate genes. Cryptic chromosome abnormalities that have been missed might be detected by array comparative genomic hybridization. METHODS In this study, samples from 42 idiopathic POF patients were subjected to a complete end-to-end X/Y chromosome tiling path array to achieve a detailed copy number variation (CNV) analysis of X chromosome involvement in POF. The arrays also contained a 1 Mb autosomal tiling path as a reference control. Quantitative PCR for selected genes contained within the CNVs was used to confirm the majority of the changes detected. The expression pattern of some of these genes in human tissue RNA was examined by reverse transcription (RT)–PCR. RESULTS A number of CNVs were identified on both Xp and Xq, with several being shared among the POF cases. Some CNVs fall within known polymorphic CNV regions, and others span previously identified POF candidate regions and genes. CONCLUSIONS The new data reported in this study reveal further discrete X chromosome intervals not previously associated with the disease and therefore implicate new clusters of candidate genes. Further studies will be required to elucidate their involvement in POF. PMID:20570974

Detection of doublecortin domain-containing 2 (DCDC2), a new candidate tumor suppressor gene of hepatocellular carcinoma, by triple combination array analysis

PubMed Central

2013-01-01

Background To detect genes correlated with hepatocellular carcinoma (HCC), we developed a triple combination array consisting of methylation array, gene expression array and single nucleotide polymorphism (SNP) array analysis. Methods A surgical specimen obtained from a 68-year-old female HCC patient was analyzed by triple combination array, which identified doublecortin domain-containing 2 (DCDC2) as a candidate tumor suppressor gene of HCC. Subsequently, samples from 48 HCC patients were evaluated for their DCDC2 methylation and expression status using methylation specific PCR (MSP) and semi-quantitative reverse transcriptase (RT) PCR, respectively. Then, we investigated the relationship between clinicopathological factors and methylation status of DCDC2. Results DCDC2 was revealed to be hypermethylated (methylation value 0.846, range 0–1.0) in cancer tissue, compared with adjacent normal tissue (0.212) by methylation array in the 68-year-old female patient. Expression array showed decreased expression of DCDC2 in cancerous tissue. SNP array showed that the copy number of chromosome 6p22.1, in which DCDC2 resides, was normal. MSP revealed hypermethylation of the promoter region of DCDC2 in 41 of the tumor samples. DCDC2 expression was significantly decreased in the cases with methylation (P = 0.048). Furthermore, the methylated cases revealed worse prognosis for overall survival than unmethylated cases (P = 0.048). Conclusions The present study indicates that triple combination array is an effective method to detect novel genes related to HCC. We propose that DCDC2 is a tumor suppressor gene of HCC. PMID:24034596

Detection of gene communities in multi-networks reveals cancer drivers

NASA Astrophysics Data System (ADS)

Cantini, Laura; Medico, Enzo; Fortunato, Santo; Caselle, Michele

2015-12-01

We propose a new multi-network-based strategy to integrate different layers of genomic information and use them in a coordinate way to identify driving cancer genes. The multi-networks that we consider combine transcription factor co-targeting, microRNA co-targeting, protein-protein interaction and gene co-expression networks. The rationale behind this choice is that gene co-expression and protein-protein interactions require a tight coregulation of the partners and that such a fine tuned regulation can be obtained only combining both the transcriptional and post-transcriptional layers of regulation. To extract the relevant biological information from the multi-network we studied its partition into communities. To this end we applied a consensus clustering algorithm based on state of art community detection methods. Even if our procedure is valid in principle for any pathology in this work we concentrate on gastric, lung, pancreas and colorectal cancer and identified from the enrichment analysis of the multi-network communities a set of candidate driver cancer genes. Some of them were already known oncogenes while a few are new. The combination of the different layers of information allowed us to extract from the multi-network indications on the regulatory pattern and functional role of both the already known and the new candidate driver genes.

Bacterial reference genes for gene expression studies by RT-qPCR: survey and analysis.

PubMed

Rocha, Danilo J P; Santos, Carolina S; Pacheco, Luis G C

2015-09-01

The appropriate choice of reference genes is essential for accurate normalization of gene expression data obtained by the method of reverse transcription quantitative real-time PCR (RT-qPCR). In 2009, a guideline called the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) highlighted the importance of the selection and validation of more than one suitable reference gene for obtaining reliable RT-qPCR results. Herein, we searched the recent literature in order to identify the bacterial reference genes that have been most commonly validated in gene expression studies by RT-qPCR (in the first 5 years following publication of the MIQE guidelines). Through a combination of different search parameters with the text mining tool MedlineRanker, we identified 145 unique bacterial genes that were recently tested as candidate reference genes. Of these, 45 genes were experimentally validated and, in most of the cases, their expression stabilities were verified using the software tools geNorm and NormFinder. It is noteworthy that only 10 of these reference genes had been validated in two or more of the studies evaluated. An enrichment analysis using Gene Ontology classifications demonstrated that genes belonging to the functional categories of DNA Replication (GO: 0006260) and Transcription (GO: 0006351) rendered a proportionally higher number of validated reference genes. Three genes in the former functional class were also among the top five most stable genes identified through an analysis of gene expression data obtained from the Pathosystems Resource Integration Center. These results may provide a guideline for the initial selection of candidate reference genes for RT-qPCR studies in several different bacterial species.

Immune Profiles to Predict Response to Desensitization Therapy in Highly HLA-Sensitized Kidney Transplant Candidates

PubMed Central

Yabu, Julie M.; Siebert, Janet C.; Maecker, Holden T.

2016-01-01

Background Kidney transplantation is the most effective treatment for end-stage kidney disease. Sensitization, the formation of human leukocyte antigen (HLA) antibodies, remains a major barrier to successful kidney transplantation. Despite the implementation of desensitization strategies, many candidates fail to respond. Current progress is hindered by the lack of biomarkers to predict response and to guide therapy. Our objective was to determine whether differences in immune and gene profiles may help identify which candidates will respond to desensitization therapy. Methods and Findings Single-cell mass cytometry by time-of-flight (CyTOF) phenotyping, gene arrays, and phosphoepitope flow cytometry were performed in a study of 20 highly sensitized kidney transplant candidates undergoing desensitization therapy. Responders to desensitization therapy were defined as 5% or greater decrease in cumulative calculated panel reactive antibody (cPRA) levels, and non-responders had 0% decrease in cPRA. Using a decision tree analysis, we found that a combination of transitional B cell and regulatory T cell (Treg) frequencies at baseline before initiation of desensitization therapy could distinguish responders from non-responders. Using a support vector machine (SVM) and longitudinal data, TRAF3IP3 transcripts and HLA-DR-CD38+CD4+ T cells could also distinguish responders from non-responders. Combining all assays in a multivariate analysis and elastic net regression model with 72 analytes, we identified seven that were highly interrelated and eleven that predicted response to desensitization therapy. Conclusions Measuring baseline and longitudinal immune and gene profiles could provide a useful strategy to distinguish responders from non-responders to desensitization therapy. This study presents the integration of novel translational studies including CyTOF immunophenotyping in a multivariate analysis model that has potential applications to predict response to desensitization, select candidates, and personalize medicine to ultimately improve overall outcomes in highly sensitized kidney transplant candidates. PMID:27078882

A Genome-Wide Association Study for Culm Cellulose Content in Barley Reveals Candidate Genes Co-Expressed with Members of the CELLULOSE SYNTHASE A Gene Family

PubMed Central

Houston, Kelly; Burton, Rachel A.; Sznajder, Beata; Rafalski, Antoni J.; Dhugga, Kanwarpal S.; Mather, Diane E.; Taylor, Jillian; Steffenson, Brian J.; Waugh, Robbie; Fincher, Geoffrey B.

2015-01-01

Cellulose is a fundamentally important component of cell walls of higher plants. It provides a scaffold that allows the development and growth of the plant to occur in an ordered fashion. Cellulose also provides mechanical strength, which is crucial for both normal development and to enable the plant to withstand both abiotic and biotic stresses. We quantified the cellulose concentration in the culm of 288 two – rowed and 288 six – rowed spring type barley accessions that were part of the USDA funded barley Coordinated Agricultural Project (CAP) program in the USA. When the population structure of these accessions was analysed we identified six distinct populations, four of which we considered to be comprised of a sufficient number of accessions to be suitable for genome-wide association studies (GWAS). These lines had been genotyped with 3072 SNPs so we combined the trait and genetic data to carry out GWAS. The analysis allowed us to identify regions of the genome containing significant associations between molecular markers and cellulose concentration data, including one region cross-validated in multiple populations. To identify candidate genes we assembled the gene content of these regions and used these to query a comprehensive RNA-seq based gene expression atlas. This provided us with gene annotations and associated expression data across multiple tissues, which allowed us to formulate a supported list of candidate genes that regulate cellulose biosynthesis. Several regions identified by our analysis contain genes that are co-expressed with CELLULOSE SYNTHASE A (HvCesA) across a range of tissues and developmental stages. These genes are involved in both primary and secondary cell wall development. In addition, genes that have been previously linked with cellulose synthesis by biochemical methods, such as HvCOBRA, a gene of unknown function, were also associated with cellulose levels in the association panel. Our analyses provide new insights into the genes that contribute to cellulose content in cereal culms and to a greater understanding of the interactions between them. PMID:26154104

Knowledge Discovery in Biological Databases for Revealing Candidate Genes Linked to Complex Phenotypes.

PubMed

Hassani-Pak, Keywan; Rawlings, Christopher

2017-06-13

Genetics and "omics" studies designed to uncover genotype to phenotype relationships often identify large numbers of potential candidate genes, among which the causal genes are hidden. Scientists generally lack the time and technical expertise to review all relevant information available from the literature, from key model species and from a potentially wide range of related biological databases in a variety of data formats with variable quality and coverage. Computational tools are needed for the integration and evaluation of heterogeneous information in order to prioritise candidate genes and components of interaction networks that, if perturbed through potential interventions, have a positive impact on the biological outcome in the whole organism without producing negative side effects. Here we review several bioinformatics tools and databases that play an important role in biological knowledge discovery and candidate gene prioritization. We conclude with several key challenges that need to be addressed in order to facilitate biological knowledge discovery in the future.

PINTA: a web server for network-based gene prioritization from expression data

PubMed Central

Nitsch, Daniela; Tranchevent, Léon-Charles; Gonçalves, Joana P.; Vogt, Josef Korbinian; Madeira, Sara C.; Moreau, Yves

2011-01-01

PINTA (available at http://www.esat.kuleuven.be/pinta/; this web site is free and open to all users and there is no login requirement) is a web resource for the prioritization of candidate genes based on the differential expression of their neighborhood in a genome-wide protein–protein interaction network. Our strategy is meant for biological and medical researchers aiming at identifying novel disease genes using disease specific expression data. PINTA supports both candidate gene prioritization (starting from a user defined set of candidate genes) as well as genome-wide gene prioritization and is available for five species (human, mouse, rat, worm and yeast). As input data, PINTA only requires disease specific expression data, whereas various platforms (e.g. Affymetrix) are supported. As a result, PINTA computes a gene ranking and presents the results as a table that can easily be browsed and downloaded by the user. PMID:21602267

How Artificial Intelligence Can Improve Our Understanding of the Genes Associated with Endometriosis: Natural Language Processing of the PubMed Database

PubMed Central

Mashiach, R.; Cohen, S.; Kedem, A.; Baron, A.; Zajicek, M.; Feldman, I.; Seidman, D.; Soriano, D.

2018-01-01

Endometriosis is a disease characterized by the development of endometrial tissue outside the uterus, but its cause remains largely unknown. Numerous genes have been studied and proposed to help explain its pathogenesis. However, the large number of these candidate genes has made functional validation through experimental methodologies nearly impossible. Computational methods could provide a useful alternative for prioritizing those most likely to be susceptibility genes. Using artificial intelligence applied to text mining, this study analyzed the genes involved in the pathogenesis, development, and progression of endometriosis. The data extraction by text mining of the endometriosis-related genes in the PubMed database was based on natural language processing, and the data were filtered to remove false positives. Using data from the text mining and gene network information as input for the web-based tool, 15,207 endometriosis-related genes were ranked according to their score in the database. Characterization of the filtered gene set through gene ontology, pathway, and network analysis provided information about the numerous mechanisms hypothesized to be responsible for the establishment of ectopic endometrial tissue, as well as the migration, implantation, survival, and proliferation of ectopic endometrial cells. Finally, the human genome was scanned through various databases using filtered genes as a seed to determine novel genes that might also be involved in the pathogenesis of endometriosis but which have not yet been characterized. These genes could be promising candidates to serve as useful diagnostic biomarkers and therapeutic targets in the management of endometriosis. PMID:29750165

How Artificial Intelligence Can Improve Our Understanding of the Genes Associated with Endometriosis: Natural Language Processing of the PubMed Database.

PubMed

Bouaziz, J; Mashiach, R; Cohen, S; Kedem, A; Baron, A; Zajicek, M; Feldman, I; Seidman, D; Soriano, D

2018-01-01

Endometriosis is a disease characterized by the development of endometrial tissue outside the uterus, but its cause remains largely unknown. Numerous genes have been studied and proposed to help explain its pathogenesis. However, the large number of these candidate genes has made functional validation through experimental methodologies nearly impossible. Computational methods could provide a useful alternative for prioritizing those most likely to be susceptibility genes. Using artificial intelligence applied to text mining, this study analyzed the genes involved in the pathogenesis, development, and progression of endometriosis. The data extraction by text mining of the endometriosis-related genes in the PubMed database was based on natural language processing, and the data were filtered to remove false positives. Using data from the text mining and gene network information as input for the web-based tool, 15,207 endometriosis-related genes were ranked according to their score in the database. Characterization of the filtered gene set through gene ontology, pathway, and network analysis provided information about the numerous mechanisms hypothesized to be responsible for the establishment of ectopic endometrial tissue, as well as the migration, implantation, survival, and proliferation of ectopic endometrial cells. Finally, the human genome was scanned through various databases using filtered genes as a seed to determine novel genes that might also be involved in the pathogenesis of endometriosis but which have not yet been characterized. These genes could be promising candidates to serve as useful diagnostic biomarkers and therapeutic targets in the management of endometriosis.

Identification of Human Disease Genes from Interactome Network Using Graphlet Interaction

PubMed Central

Yang, Lun; Wei, Dong-Qing; Qi, Ying-Xin; Jiang, Zong-Lai

2014-01-01

Identifying genes related to human diseases, such as cancer and cardiovascular disease, etc., is an important task in biomedical research because of its applications in disease diagnosis and treatment. Interactome networks, especially protein-protein interaction networks, had been used to disease genes identification based on the hypothesis that strong candidate genes tend to closely relate to each other in some kinds of measure on the network. We proposed a new measure to analyze the relationship between network nodes which was called graphlet interaction. The graphlet interaction contained 28 different isomers. The results showed that the numbers of the graphlet interaction isomers between disease genes in interactome networks were significantly larger than random picked genes, while graphlet signatures were not. Then, we designed a new type of score, based on the network properties, to identify disease genes using graphlet interaction. The genes with higher scores were more likely to be disease genes, and all candidate genes were ranked according to their scores. Then the approach was evaluated by leave-one-out cross-validation. The precision of the current approach achieved 90% at about 10% recall, which was apparently higher than the previous three predominant algorithms, random walk, Endeavour and neighborhood based method. Finally, the approach was applied to predict new disease genes related to 4 common diseases, most of which were identified by other independent experimental researches. In conclusion, we demonstrate that the graphlet interaction is an effective tool to analyze the network properties of disease genes, and the scores calculated by graphlet interaction is more precise in identifying disease genes. PMID:24465923

Identifying positive selection candidate loci for high-altitude adaptation in Andean populations

PubMed Central

2009-01-01

High-altitude environments (>2,500 m) provide scientists with a natural laboratory to study the physiological and genetic effects of low ambient oxygen tension on human populations. One approach to understanding how life at high altitude has affected human metabolism is to survey genome-wide datasets for signatures of natural selection. In this work, we report on a study to identify selection-nominated candidate genes involved in adaptation to hypoxia in one highland group, Andeans from the South American Altiplano. We analysed dense microarray genotype data using four test statistics that detect departures from neutrality. Using a candidate gene, single nucleotide polymorphism-based approach, we identified genes exhibiting preliminary evidence of recent genetic adaptation in this population. These included genes that are part of the hypoxia-inducible transcription factor (HIF) pathway, a biochemical pathway involved in oxygen homeostasis, as well as three other genomic regions previously not known to be associated with high-altitude phenotypes. In addition to identifying selection-nominated candidate genes, we also tested whether the HIF pathway shows evidence of natural selection. Our results indicate that the genes of this biochemical pathway as a group show no evidence of having evolved in response to hypoxia in Andeans. Results from particular HIF-targeted genes, however, suggest that genes in this pathway could play a role in Andean adaptation to high altitude, even if the pathway as a whole does not show higher relative rates of evolution. These data suggest a genetic role in high-altitude adaptation and provide a basis for genotype/phenotype association studies that are necessary to confirm the role of putative natural selection candidate genes and gene regions in adaptation to altitude. PMID:20038496

Analysis of 60 reported glioma risk SNPs replicates published GWAS findings but fails to replicate associations from published candidate-gene studies.

PubMed

Walsh, Kyle M; Anderson, Erik; Hansen, Helen M; Decker, Paul A; Kosel, Matt L; Kollmeyer, Thomas; Rice, Terri; Zheng, Shichun; Xiao, Yuanyuan; Chang, Jeffrey S; McCoy, Lucie S; Bracci, Paige M; Wiemels, Joe L; Pico, Alexander R; Smirnov, Ivan; Lachance, Daniel H; Sicotte, Hugues; Eckel-Passow, Jeanette E; Wiencke, John K; Jenkins, Robert B; Wrensch, Margaret R

2013-02-01

Genomewide association studies (GWAS) and candidate-gene studies have implicated single-nucleotide polymorphisms (SNPs) in at least 45 different genes as putative glioma risk factors. Attempts to validate these associations have yielded variable results and few genetic risk factors have been consistently replicated. We conducted a case-control study of Caucasian glioma cases and controls from the University of California San Francisco (810 cases, 512 controls) and the Mayo Clinic (852 cases, 789 controls) in an attempt to replicate previously reported genetic risk factors for glioma. Sixty SNPs selected from the literature (eight from GWAS and 52 from candidate-gene studies) were successfully genotyped on an Illumina custom genotyping panel. Eight SNPs in/near seven different genes (TERT, EGFR, CCDC26, CDKN2A, PHLDB1, RTEL1, TP53) were significantly associated with glioma risk in the combined dataset (P < 0.05), with all associations in the same direction as in previous reports. Several SNP associations showed considerable differences across histologic subtype. All eight successfully replicated associations were first identified by GWAS, although none of the putative risk SNPs from candidate-gene studies was associated in the full case-control sample (all P values > 0.05). Although several confirmed associations are located near genes long known to be involved in gliomagenesis (e.g., EGFR, CDKN2A, TP53), these associations were first discovered by the GWAS approach and are in noncoding regions. These results highlight that the deficiencies of the candidate-gene approach lay in selecting both appropriate genes and relevant SNPs within these genes. © 2012 WILEY PERIODICALS, INC.

Validating internal controls for quantitative plant gene expression studies

PubMed Central

Brunner, Amy M; Yakovlev, Igor A; Strauss, Steven H

2004-01-01

Background Real-time reverse transcription PCR (RT-PCR) has greatly improved the ease and sensitivity of quantitative gene expression studies. However, accurate measurement of gene expression with this method relies on the choice of a valid reference for data normalization. Studies rarely verify that gene expression levels for reference genes are adequately consistent among the samples used, nor compare alternative genes to assess which are most reliable for the experimental conditions analyzed. Results Using real-time RT-PCR to study the expression of 10 poplar (genus Populus) housekeeping genes, we demonstrate a simple method for determining the degree of stability of gene expression over a set of experimental conditions. Based on a traditional method for analyzing the stability of varieties in plant breeding, it defines measures of gene expression stability from analysis of variance (ANOVA) and linear regression. We found that the potential internal control genes differed widely in their expression stability over the different tissues, developmental stages and environmental conditions studied. Conclusion Our results support that quantitative comparisons of candidate reference genes are an important part of real-time RT-PCR studies that seek to precisely evaluate variation in gene expression. The method we demonstrated facilitates statistical and graphical evaluation of gene expression stability. Selection of the best reference gene for a given set of experimental conditions should enable detection of biologically significant changes in gene expression that are too small to be revealed by less precise methods, or when highly variable reference genes are unknowingly used in real-time RT-PCR experiments. PMID:15317655

Candidate EDA targets revealed by expression profiling of primary keratinocytes from Tabby mutant mice

PubMed Central

Esibizione, Diana; Cui, Chang-Yi; Schlessinger, David

2009-01-01

EDA, the gene mutated in anhidrotic ectodermal dysplasia, encodes ectodysplasin, a TNF superfamily member that activates NF-kB mediated transcription. To identify EDA target genes, we have earlier used expression profiling to infer genes differentially expressed at various developmental time points in Tabby (Eda-deficient) compared to wild-type mouse skin. To increase the resolution to find genes whose expression may be restricted to epidermal cells, we have now extended studies to primary keratinocyte cultures established from E19 wild-type and Tabby skin. Using microarrays bearing 44,000 gene probes, we found 385 preliminary candidate genes whose expression was significantly affected by Eda loss. By comparing expression profiles to those from Eda-A1 transgenic skin, we restricted the list to 38 “candidate EDA targets”, 14 of which were already known to be expressed in hair follicles or epidermis. We confirmed expression changes for 3 selected genes, Tbx1, Bmp7, and Jag1, both in keratinocytes and in whole skin, by Q-PCR and Western blotting analyses. Thus, by the analysis of keratinocytes, novel candidate pathways downstream of EDA were detected. PMID:18848976

A comprehensive study of the genomic differentiation between temperate Dent and Flint maize.

PubMed

Unterseer, Sandra; Pophaly, Saurabh D; Peis, Regina; Westermeier, Peter; Mayer, Manfred; Seidel, Michael A; Haberer, Georg; Mayer, Klaus F X; Ordas, Bernardo; Pausch, Hubert; Tellier, Aurélien; Bauer, Eva; Schön, Chris-Carolin

2016-07-08

Dent and Flint represent two major germplasm pools exploited in maize breeding. Several traits differentiate the two pools, like cold tolerance, early vigor, and flowering time. A comparative investigation of their genomic architecture relevant for quantitative trait expression has not been reported so far. Understanding the genomic differences between germplasm pools may contribute to a better understanding of the complementarity in heterotic patterns exploited in hybrid breeding and of mechanisms involved in adaptation to different environments. We perform whole-genome screens for signatures of selection specific to temperate Dent and Flint maize by comparing high-density genotyping data of 70 American and European Dent and 66 European Flint inbred lines. We find 2.2 % and 1.4 % of the genes are under selective pressure, respectively, and identify candidate genes associated with agronomic traits known to differ between the two pools. Taking flowering time as an example for the differentiation between Dent and Flint, we investigate candidate genes involved in the flowering network by phenotypic analyses in a Dent-Flint introgression library and find that the Flint haplotypes of the candidates promote earlier flowering. Within the flowering network, the majority of Flint candidates are associated with endogenous pathways in contrast to Dent candidate genes, which are mainly involved in response to environmental factors like light and photoperiod. The diversity patterns of the candidates in a unique panel of more than 900 individuals from 38 European landraces indicate a major contribution of landraces from France, Germany, and Spain to the candidate gene diversity of the Flint elite lines. In this study, we report the investigation of pool-specific differences between temperate Dent and Flint on a genome-wide scale. The identified candidate genes represent a promising source for the functional investigation of pool-specific haplotypes in different genetic backgrounds and for the evaluation of their potential for future crop improvement like the adaptation to specific environments.

Identification of candidate genes associated with fibromyalgia susceptibility in southern Spanish women: the al-Ándalus project.

PubMed

Estévez-López, Fernando; Camiletti-Moirón, Daniel; Aparicio, Virginia A; Segura-Jiménez, Víctor; Álvarez-Gallardo, Inmaculada C; Soriano-Maldonado, Alberto; Borges-Cosic, Milkana; Acosta-Manzano, Pedro; Geenen, Rinie; Delgado-Fernández, Manuel; Martínez-González, Luis J; Ruiz, Jonatan R; Álvarez-Cubero, María J

2018-02-27

Candidate-gene studies on fibromyalgia susceptibility often include a small number of single nucleotide polymorphisms (SNPs), which is a limitation. Moreover, there is a paucity of evidence in Europe. Therefore, we compared genotype frequencies of candidate SNPs in a well-characterised sample of Spanish women with fibromyalgia and healthy non-fibromyalgia women. A total of 314 women with a diagnosis of fibromyalgia (cases) and 112 non-fibromyalgia healthy (controls) women participated in this candidate-gene study. Buccal swabs were collected for DNA extraction. Using TaqMan™ OpenArray™, we analysed 61 SNPs of 33 genes related to fibromyalgia susceptibility, symptoms, or potential mechanisms. We observed that the rs841 and rs1799971 GG genotype was more frequently observed in fibromyalgia than in controls (p = 0.04 and p = 0.02, respectively). The rs2097903 AT/TT genotypes were also more often present in the fibromyalgia participants than in their control peers (p = 0.04). There were no differences for the remaining SNPs. We identified, for the first time, associations of the rs841 (guanosine triphosphate cyclohydrolase 1 gene) and rs2097903 (catechol-O-methyltransferase gene) SNPs with higher risk of fibromyalgia susceptibility. We also confirmed that the rs1799971 SNP (opioid receptor μ1 gene) might confer genetic risk of fibromyalgia. We did not adjust for multiple comparisons, which would be too stringent and yield to non-significant differences in the genotype frequencies between cases and controls. Our findings may be biologically meaningful and informative, and should be further investigated in other populations. Of particular interest is to replicate the present study in a larger independent sample to confirm or refute our findings. On the other hand, by including 61 SNPs of 33 candidate-genes with a strong rationale (they were previously investigated in relation to fibromyalgia susceptibility, symptoms or potential mechanisms), the present research is the most comprehensive candidate-gene study on fibromyalgia susceptibility to date.

High-throughput detection and screening of plants modified by gene editing using quantitative real-time polymerase chain reaction.

PubMed

Peng, Cheng; Wang, Hua; Xu, Xiaoli; Wang, Xiaofu; Chen, Xiaoyun; Wei, Wei; Lai, Yongmin; Liu, Guoquan; Godwin, Ian Douglas; Li, Jieqin; Zhang, Ling; Xu, Junfeng

2018-05-15

Gene editing techniques are becoming powerful tools for modifying target genes in organisms. Although several methods have been developed to detect gene-edited organisms, these techniques are time and labour intensive. Meanwhile, few studies have investigated high-throughput detection and screening strategies for plants modified by gene editing. In this study, we developed a simple, sensitive and high-throughput quantitative real-time (qPCR)-based method. The qPCR-based method exploits two differently labelled probes that are placed within one amplicon at the gene editing target site to simultaneously detect the wild-type and a gene-edited mutant. We showed that the qPCR-based method can accurately distinguish CRISPR/Cas9-induced mutants from the wild-type in several different plant species, such as Oryza sativa, Arabidopsis thaliana, Sorghum bicolor, and Zea mays. Moreover, the method can subsequently determine the mutation type by direct sequencing of the qPCR products of mutations due to gene editing. The qPCR-based method is also sufficiently sensitive to distinguish between heterozygous and homozygous mutations in T 0 transgenic plants. In a 384-well plate format, the method enabled the simultaneous analysis of up to 128 samples in three replicates without handling the post-polymerase chain reaction (PCR) products. Thus, we propose that our method is an ideal choice for screening plants modified by gene editing from many candidates in T 0 transgenic plants, which will be widely used in the area of plant gene editing. © 2018 The Authors The Plant Journal © 2018 John Wiley & Sons Ltd.

Genome-wide patterns of genetic distances reveal candidate Loci contributing to human population-specific traits.

PubMed

de Magalhães, João Pedro; Matsuda, Alex

2012-03-01

Modern humans originated in Africa before migrating across the world with founder effects and adaptations to new environments contributing to their present phenotypic diversity. Determining the genetic basis of differences between populations may provide clues about our evolutionary history and may have clinical implications. Herein, we develop a method to detect genes and biological processes in which populations most differ by calculating the genetic distance between modern populations and a hypothetical ancestral population. We apply our method to large-scale single nucleotide polymorphism (SNP) data from human populations of African, European and Asian origin. As expected, ancestral alleles were more conserved in the African populations and we found evidence of high divergence in genes previously suggested as targets of selection related to skin pigmentation, immune response, senses and dietary adaptations. Our genome-wide scan also reveals novel candidates for contributing to population-specific traits. These include genes related to neuronal development and behavior that may have been influenced by cultural processes. Moreover, in the African populations, we found a high divergence in genes related to UV protection and to the male reproductive system. Taken together, these results confirm and expand previous findings, providing new clues about the evolution and genetics of human phenotypic diversity. © 2011 The Authors Annals of Human Genetics © 2011 Blackwell Publishing Ltd/University College London.

Comparative molecular analyses of select pH- and osmoregulatory genes in three freshwater crayfish Cherax quadricarinatus, C. destructor and C. cainii.

PubMed

Ali, Muhammad Y; Pavasovic, Ana; Dammannagoda, Lalith K; Mather, Peter B; Prentis, Peter J

2017-01-01

Systemic acid-base balance and osmotic/ionic regulation in decapod crustaceans are in part maintained by a set of transport-related enzymes such as carbonic anhydrase (CA), Na + /K + -ATPase (NKA), H + -ATPase (HAT), Na + /K + /2Cl - cotransporter (NKCC), Na + /Cl - /HCO[Formula: see text] cotransporter (NBC), Na + /H + exchanger (NHE), Arginine kinase (AK), Sarcoplasmic Ca +2 -ATPase (SERCA) and Calreticulin (CRT). We carried out a comparative molecular analysis of these genes in three commercially important yet eco-physiologically distinct freshwater crayfish , Cherax quadricarinatus, C. destructor and C. cainii , with the aim to identify mutations in these genes and determine if observed patterns of mutations were consistent with the action of natural selection. We also conducted a tissue-specific expression analysis of these genes across seven different organs, including gills, hepatopancreas, heart, kidney, liver, nerve and testes using NGS transcriptome data. The molecular analysis of the candidate genes revealed a high level of sequence conservation across the three Cherax sp. Hyphy analysis revealed that all candidate genes showed patterns of molecular variation consistent with neutral evolution. The tissue-specific expression analysis showed that 46% of candidate genes were expressed in all tissue types examined, while approximately 10% of candidate genes were only expressed in a single tissue type. The largest number of genes was observed in nerve (84%) and gills (78%) and the lowest in testes (66%). The tissue-specific expression analysis also revealed that most of the master genes regulating pH and osmoregulation (CA, NKA, HAT, NKCC, NBC, NHE) were expressed in all tissue types indicating an important physiological role for these genes outside of osmoregulation in other tissue types. The high level of sequence conservation observed in the candidate genes may be explained by the important role of these genes as well as potentially having a number of other basic physiological functions in different tissue types.

Gene doping in sports.

PubMed

Unal, Mehmet; Ozer Unal, Durisehvar

2004-01-01

Gene or cell doping is defined by the World Anti-Doping Agency (WADA) as "the non-therapeutic use of genes, genetic elements and/or cells that have the capacity to enhance athletic performance". New research in genetics and genomics will be used not only to diagnose and treat disease, but also to attempt to enhance human performance. In recent years, gene therapy has shown progress and positive results that have highlighted the potential misuse of this technology and the debate of 'gene doping'. Gene therapies developed for the treatment of diseases such as anaemia (the gene for erythropoietin), muscular dystrophy (the gene for insulin-like growth factor-1) and peripheral vascular diseases (the gene for vascular endothelial growth factor) are potential doping methods. With progress in gene technology, many other genes with this potential will be discovered. For this reason, it is important to develop timely legal regulations and to research the field of gene doping in order to develop methods of detection. To protect the health of athletes and to ensure equal competitive conditions, the International Olympic Committee, WADA and International Sports Federations have accepted performance-enhancing substances and methods as being doping, and have forbidden them. Nevertheless, the desire to win causes athletes to misuse these drugs and methods. This paper reviews the current status of gene doping and candidate performance enhancement genes, and also the use of gene therapy in sports medicine and ethics of genetic enhancement. Copyright 2004 Adis Data Information BV

Identification of homogeneous genetic architecture of multiple genetically correlated traits by block clustering of genome-wide associations.

PubMed

Gupta, Mayetri; Cheung, Ching-Lung; Hsu, Yi-Hsiang; Demissie, Serkalem; Cupples, L Adrienne; Kiel, Douglas P; Karasik, David

2011-06-01

Genome-wide association studies (GWAS) using high-density genotyping platforms offer an unbiased strategy to identify new candidate genes for osteoporosis. It is imperative to be able to clearly distinguish signal from noise by focusing on the best phenotype in a genetic study. We performed GWAS of multiple phenotypes associated with fractures [bone mineral density (BMD), bone quantitative ultrasound (QUS), bone geometry, and muscle mass] with approximately 433,000 single-nucleotide polymorphisms (SNPs) and created a database of resulting associations. We performed analysis of GWAS data from 23 phenotypes by a novel modification of a block clustering algorithm followed by gene-set enrichment analysis. A data matrix of standardized regression coefficients was partitioned along both axes--SNPs and phenotypes. Each partition represents a distinct cluster of SNPs that have similar effects over a particular set of phenotypes. Application of this method to our data shows several SNP-phenotype connections. We found a strong cluster of association coefficients of high magnitude for 10 traits (BMD at several skeletal sites, ultrasound measures, cross-sectional bone area, and section modulus of femoral neck and shaft). These clustered traits were highly genetically correlated. Gene-set enrichment analyses indicated the augmentation of genes that cluster with the 10 osteoporosis-related traits in pathways such as aldosterone signaling in epithelial cells, role of osteoblasts, osteoclasts, and chondrocytes in rheumatoid arthritis, and Parkinson signaling. In addition to several known candidate genes, we also identified PRKCH and SCNN1B as potential candidate genes for multiple bone traits. In conclusion, our mining of GWAS results revealed the similarity of association results between bone strength phenotypes that may be attributed to pleiotropic effects of genes. This knowledge may prove helpful in identifying novel genes and pathways that underlie several correlated phenotypes, as well as in deciphering genetic and phenotypic modularity underlying osteoporosis risk. Copyright © 2011 American Society for Bone and Mineral Research.

Identification of an miRNA candidate reflects the possible significance of transcribed microsatellites in the hairpin precursors of black pepper.

PubMed

Joy, Nisha; Soniya, Eppurathu Vasudevan

2012-06-01

Plant miRNAs (18-24nt) are generated by the RNase III-type Dicer endonuclease from the endogenous hairpin precursors ('pre-miRNAs') with significant regulatory functions. The transcribed regions display a higher frequency of microsatellites, when compared to other regions of the genomic DNA. Simple sequence repeats (SSRs) resulting from replication slippage occurring in transcripts affect the expression of genes. The available experimental evidence for the incidence of SSRs in the miRNA precursors is limited. Considering the potential significance of SSRs in the miRNA genes, we carried out a preliminary analysis to verify the presence of SSRs in the pri-miRNAs of black pepper (Piper nigrum L.). We isolated a (CT) dinucleotide SSR bearing transcript using SMART strategy. The transcript was predicted to be a 'pri-miRNA candidate' with Dicer sites based on miRNA prediction tools and MFOLD structural predictions. The presence of this 'miRNA candidate' was confirmed by real-time TaqMan assays. The upstream sequence of the 'miRNA candidate' by genome walking when subjected to PlantCARE showed the presence of certain promoter elements, and the deduced amino acid showed significant similarity with NAP1 gene, which affects the transcription of many genes. Moreover the hairpin-like precursor overlapped the neighbouring NAP1 gene. In silico analysis revealed distinct putative functions for the 'miRNA candidate', of which majority were related to growth. Hence, we assume that this 'miRNA candidate' may get activated during transcription of NAP gene, thereby regulating the expression of many genes involved in developmental processes.

Detection of biomarkers for Hepatocellular Carcinoma using a hybrid univariate gene selection methods

PubMed Central

2012-01-01

Background Discovering new biomarkers has a great role in improving early diagnosis of Hepatocellular carcinoma (HCC). The experimental determination of biomarkers needs a lot of time and money. This motivates this work to use in-silico prediction of biomarkers to reduce the number of experiments required for detecting new ones. This is achieved by extracting the most representative genes in microarrays of HCC. Results In this work, we provide a method for extracting the differential expressed genes, up regulated ones, that can be considered candidate biomarkers in high throughput microarrays of HCC. We examine the power of several gene selection methods (such as Pearson’s correlation coefficient, Cosine coefficient, Euclidean distance, Mutual information and Entropy with different estimators) in selecting informative genes. A biological interpretation of the highly ranked genes is done using KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways, ENTREZ and DAVID (Database for Annotation, Visualization, and Integrated Discovery) databases. The top ten genes selected using Pearson’s correlation coefficient and Cosine coefficient contained six genes that have been implicated in cancer (often multiple cancers) genesis in previous studies. A fewer number of genes were obtained by the other methods (4 genes using Mutual information, 3genes using Euclidean distance and only one gene using Entropy). A better result was obtained by the utilization of a hybrid approach based on intersecting the highly ranked genes in the output of all investigated methods. This hybrid combination yielded seven genes (2 genes for HCC and 5 genes in different types of cancer) in the top ten genes of the list of intersected genes. Conclusions To strengthen the effectiveness of the univariate selection methods, we propose a hybrid approach by intersecting several of these methods in a cascaded manner. This approach surpasses all of univariate selection methods when used individually according to biological interpretation and the examination of gene expression signal profiles. PMID:22867264

An automatic and efficient pipeline for disease gene identification through utilizing family-based sequencing data.

PubMed

Song, Dandan; Li, Ning; Liao, Lejian

2015-01-01

Due to the generation of enormous amounts of data at both lower costs as well as in shorter times, whole-exome sequencing technologies provide dramatic opportunities for identifying disease genes implicated in Mendelian disorders. Since upwards of thousands genomic variants can be sequenced in each exome, it is challenging to filter pathogenic variants in protein coding regions and reduce the number of missing true variants. Therefore, an automatic and efficient pipeline for finding disease variants in Mendelian disorders is designed by exploiting a combination of variants filtering steps to analyze the family-based exome sequencing approach. Recent studies on the Freeman-Sheldon disease are revisited and show that the proposed method outperforms other existing candidate gene identification methods.

Identification of new candidate drugs for lung cancer using chemical-chemical interactions, chemical-protein interactions and a K-means clustering algorithm.

PubMed

Lu, Jing; Chen, Lei; Yin, Jun; Huang, Tao; Bi, Yi; Kong, Xiangyin; Zheng, Mingyue; Cai, Yu-Dong

2016-01-01

Lung cancer, characterized by uncontrolled cell growth in the lung tissue, is the leading cause of global cancer deaths. Until now, effective treatment of this disease is limited. Many synthetic compounds have emerged with the advancement of combinatorial chemistry. Identification of effective lung cancer candidate drug compounds among them is a great challenge. Thus, it is necessary to build effective computational methods that can assist us in selecting for potential lung cancer drug compounds. In this study, a computational method was proposed to tackle this problem. The chemical-chemical interactions and chemical-protein interactions were utilized to select candidate drug compounds that have close associations with approved lung cancer drugs and lung cancer-related genes. A permutation test and K-means clustering algorithm were employed to exclude candidate drugs with low possibilities to treat lung cancer. The final analysis suggests that the remaining drug compounds have potential anti-lung cancer activities and most of them have structural dissimilarity with approved drugs for lung cancer.

A large-scale RNA interference screen identifies genes that regulate autophagy at different stages.

PubMed

Guo, Sujuan; Pridham, Kevin J; Virbasius, Ching-Man; He, Bin; Zhang, Liqing; Varmark, Hanne; Green, Michael R; Sheng, Zhi

2018-02-12

Dysregulated autophagy is central to the pathogenesis and therapeutic development of cancer. However, how autophagy is regulated in cancer is not well understood and genes that modulate cancer autophagy are not fully defined. To gain more insights into autophagy regulation in cancer, we performed a large-scale RNA interference screen in K562 human chronic myeloid leukemia cells using monodansylcadaverine staining, an autophagy-detecting approach equivalent to immunoblotting of the autophagy marker LC3B or fluorescence microscopy of GFP-LC3B. By coupling monodansylcadaverine staining with fluorescence-activated cell sorting, we successfully isolated autophagic K562 cells where we identified 336 short hairpin RNAs. After candidate validation using Cyto-ID fluorescence spectrophotometry, LC3B immunoblotting, and quantitative RT-PCR, 82 genes were identified as autophagy-regulating genes. 20 genes have been reported previously and the remaining 62 candidates are novel autophagy mediators. Bioinformatic analyses revealed that most candidate genes were involved in molecular pathways regulating autophagy, rather than directly participating in the autophagy process. Further autophagy flux assays revealed that 57 autophagy-regulating genes suppressed autophagy initiation, whereas 21 candidates promoted autophagy maturation. Our RNA interference screen identifies identified genes that regulate autophagy at different stages, which helps decode autophagy regulation in cancer and offers novel avenues to develop autophagy-related therapies for cancer.

Bioinformatics-Based Identification of Candidate Genes from QTLs Associated with Cell Wall Traits in Populus

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ranjan, Priya; Yin, Tongming; Zhang, Xinye

2009-11-01

Quantitative trait locus (QTL) studies are an integral part of plant research and are used to characterize the genetic basis of phenotypic variation observed in structured populations and inform marker-assisted breeding efforts. These QTL intervals can span large physical regions on a chromosome comprising hundreds of genes, thereby hampering candidate gene identification. Genome history, evolution, and expression evidence can be used to narrow the genes in the interval to a smaller list that is manageable for detailed downstream functional genomics characterization. Our primary motivation for the present study was to address the need for a research methodology that identifies candidatemore » genes within a broad QTL interval. Here we present a bioinformatics-based approach for subdividing candidate genes within QTL intervals into alternate groups of high probability candidates. Application of this approach in the context of studying cell wall traits, specifically lignin content and S/G ratios of stem and root in Populus plants, resulted in manageable sets of genes of both known and putative cell wall biosynthetic function. These results provide a roadmap for future experimental work leading to identification of new genes controlling cell wall recalcitrance and, ultimately, in the utility of plant biomass as an energy feedstock.« less

Text Mining in Cancer Gene and Pathway Prioritization

PubMed Central

Luo, Yuan; Riedlinger, Gregory; Szolovits, Peter

2014-01-01

Prioritization of cancer implicated genes has received growing attention as an effective way to reduce wet lab cost by computational analysis that ranks candidate genes according to the likelihood that experimental verifications will succeed. A multitude of gene prioritization tools have been developed, each integrating different data sources covering gene sequences, differential expressions, function annotations, gene regulations, protein domains, protein interactions, and pathways. This review places existing gene prioritization tools against the backdrop of an integrative Omic hierarchy view toward cancer and focuses on the analysis of their text mining components. We explain the relatively slow progress of text mining in gene prioritization, identify several challenges to current text mining methods, and highlight a few directions where more effective text mining algorithms may improve the overall prioritization task and where prioritizing the pathways may be more desirable than prioritizing only genes. PMID:25392685

Text mining in cancer gene and pathway prioritization.

PubMed

Luo, Yuan; Riedlinger, Gregory; Szolovits, Peter

2014-01-01

Prioritization of cancer implicated genes has received growing attention as an effective way to reduce wet lab cost by computational analysis that ranks candidate genes according to the likelihood that experimental verifications will succeed. A multitude of gene prioritization tools have been developed, each integrating different data sources covering gene sequences, differential expressions, function annotations, gene regulations, protein domains, protein interactions, and pathways. This review places existing gene prioritization tools against the backdrop of an integrative Omic hierarchy view toward cancer and focuses on the analysis of their text mining components. We explain the relatively slow progress of text mining in gene prioritization, identify several challenges to current text mining methods, and highlight a few directions where more effective text mining algorithms may improve the overall prioritization task and where prioritizing the pathways may be more desirable than prioritizing only genes.

A data-mining approach to rank candidate protein-binding partners-The case of biogenesis of lysosome-related organelles complex-1 (BLOC-1).

PubMed

Rodriguez-Fernandez, I A; Dell'Angelica, E C

2009-04-01

The study of protein-protein interactions is a powerful approach to uncovering the molecular function of gene products associated with human disease. Protein-protein interaction data are accumulating at an unprecedented pace owing to interactomics projects, although it has been recognized that a significant fraction of these data likely represents false positives. During our studies of biogenesis of lysosome-related organelles complex-1 (BLOC-1), a protein complex involved in protein trafficking and containing the products of genes mutated in Hermansky-Pudlak syndrome, we faced the problem of having too many candidate binding partners to pursue experimentally. In this work, we have explored ways of efficiently gathering high-quality information about candidate binding partners and presenting the information in a visually friendly manner. We applied the approach to rank 70 candidate binding partners of human BLOC-1 and 102 candidates of its counterpart from Drosophila melanogaster. The top candidate for human BLOC-1 was the small GTPase encoded by the RAB11A gene, which is a paralogue of the Rab38 and Rab32 proteins in mammals and the lightoid gene product in flies. Interestingly, genetic analyses in D. melanogaster uncovered a synthetic sick/lethal interaction between Rab11 and lightoid. The data-mining approach described herein can be customized to study candidate binding partners for other proteins or possibly candidates derived from other types of 'omics' data.

Evaluation of RNA extraction methods and identification of putative reference genes for real-time quantitative polymerase chain reaction expression studies on olive (Olea europaea L.) fruits.

PubMed

Nonis, Alberto; Vezzaro, Alice; Ruperti, Benedetto

2012-07-11

Genome wide transcriptomic surveys together with targeted molecular studies are uncovering an ever increasing number of differentially expressed genes in relation to agriculturally relevant processes in olive (Olea europaea L). These data need to be supported by quantitative approaches enabling the precise estimation of transcript abundance. qPCR being the most widely adopted technique for mRNA quantification, preliminary work needs to be done to set up robust methods for extraction of fully functional RNA and for the identification of the best reference genes to obtain reliable quantification of transcripts. In this work, we have assessed different methods for their suitability for RNA extraction from olive fruits and leaves and we have evaluated thirteen potential candidate reference genes on 21 RNA samples belonging to fruit developmental/ripening series and to leaves subjected to wounding. By using two different algorithms, GAPDH2 and PP2A1 were identified as the best reference genes for olive fruit development and ripening, and their effectiveness for normalization of expression of two ripening marker genes was demonstrated.

Identification of appropriate reference genes for normalizing transcript expression by quantitative real-time PCR in Litsea cubeba.

PubMed

Lin, Liyuan; Han, Xiaojiao; Chen, Yicun; Wu, Qingke; Wang, Yangdong

2013-12-01

Quantitative real-time PCR has emerged as a highly sensitive and widely used method for detection of gene expression profiles, via which accurate detection depends on reliable normalization. Since no single control is appropriate for all experimental treatments, it is generally advocated to select suitable internal controls prior to use for normalization. This study reported the evaluation of the expression stability of twelve potential reference genes in different tissue/organs and six fruit developmental stages of Litsea cubeba in order to screen the superior internal reference genes for data normalization. Two softwares-geNorm, and NormFinder-were used to identify stability of these candidate genes. The cycle threshold difference and coefficient of variance were also calculated to evaluate the expression stability of candidate genes. F-BOX, EF1α, UBC, and TUA were selected as the most stable reference genes across 11 sample pools. F-BOX, EF1α, and EIF4α exhibited the highest expression stability in different tissue/organs and different fruit developmental stages. Besides, a combination of two stable reference genes would be sufficient for gene expression normalization in different fruit developmental stages. In addition, the relative expression profiles of DXS and DXR were evaluated by EF1α, UBC, and SAMDC. The results further validated the reliability of stable reference genes and also highlighted the importance of selecting suitable internal controls for L. cubeba. These reference genes will be of great importance for transcript normalization in future gene expression studies on L. cubeba.

Identification of essential genes in Streptococcus pneumoniae by allelic replacement mutagenesis.

PubMed

Song, Jae-Hoon; Ko, Kwan Soo; Lee, Ji-Young; Baek, Jin Yang; Oh, Won Sup; Yoon, Ha Sik; Jeong, Jin-Yong; Chun, Jongsik

2005-06-30

To find potential targets of novel antimicrobial agents, we identified essential genes of Streptococcus pneumoniae using comparative genomics and allelic replacement mutagenesis. We compared the genome of S. pneumoniae R6 with those of Bacillus subtilis, Enterococcus faecalis, Escherichia coli, and Staphylococcus aureus, and selected 693 candidate target genes with > 40% amino acid sequence identity to the corresponding genes in at least two of the other species. The 693 genes were disrupted and 133 were found to be essential for growth. Of these, 32 encoded proteins of unknown function, and we were able to identify orthologues of 22 of these genes by genomic comparisons. The experimental method used in this study is easy to perform, rapid and efficient for identifying essential genes of bacterial pathogens.

[Screening efficient siRNAs in vitro as the candidate genes for chicken anti-avian influenza virus H5N1 breeding].

PubMed

Zhang, P; Wang, J G; Wan, J G; Liu, W Q

2010-01-01

The frequent disease outbreaks caused by avian influenza virus not only affect the poultry industry but also pose a threat to human safety. To address the problem, RNA interference (RNAi) has recently been widely used as a potential antiviral approach. Transgenesis in combination with RNAi to specifically inhibit avian enza virus gene expression has been proposed to make chickens resistant to the infection. For the transgenic breeding, screening in vitro efficient siRNAs as the candidate genes is one of the most important tasks. Here, we combined an online search tool and a series of bioinformatics programs with a set of rules for designing siRNAs targeted towards different mRNA regions of H5N1 avian influenza virus. Five rational siRNAs were chosen by this method, five U6 promoter-driven shRNA expression plasmids containing the siRNA genes were constructed and used for producing stably transfected MDCK cells. The data obtained by virus titration, IFA, PI-stained flow cytometry, real-time quantitative RT-PCR, and DAS-ELISA analyses showed that all five stably transfected cell lines we re resistant to virusreplication when exposed to 100 CCID50 of avian influenza virus H5N1. Finally, most effective plasmids (pSi-604i and pSi-1597i) as the candidates for making the transgenic chickens were chosen. These findings provide baseline information on use of RNAi technique for breeding transgenic chickens resistant to avian influenza virus.

Uncovering the genetic basis of attenuation in Marek’s disease virus

USDA-ARS?s Scientific Manuscript database

While in vitro serial passage of Marek’s disease virus (MDV) is a proven method to attenuate MDV strains, the underlying genetic changes responsible for attenuation remains unknown. To identify candidate genes and mutations, a virulent MDV generated from an Md5-containing BAC clone was serially pass...

Identification of SLC20A1 and SLC15A4 among other genes as potential risk factors for combined pituitary hormone deficiency.

PubMed

Simm, Franziska; Griesbeck, Anne; Choukair, Daniela; Weiß, Birgit; Paramasivam, Nagarajan; Klammt, Jürgen; Schlesner, Matthias; Wiemann, Stefan; Martinez, Cristina; Hoffmann, Georg F; Pfäffle, Roland W; Bettendorf, Markus; Rappold, Gudrun A

2017-10-26

PurposeCombined pituitary hormone deficiency (CPHD) is characterized by a malformed or underdeveloped pituitary gland resulting in an impaired pituitary hormone secretion. Several transcription factors have been described in its etiology, but defects in known genes account for only a small proportion of cases.MethodsTo identify novel genetic causes for congenital hypopituitarism, we performed exome-sequencing studies on 10 patients with CPHD and their unaffected parents. Two candidate genes were sequenced in further 200 patients. Genotype data of known hypopituitary genes are reviewed.ResultsWe discovered 51 likely damaging variants in 38 genes; 12 of the 51 variants represent de novo events (24%); 11 of the 38 genes (29%) were present in the E12.5/E14.5 pituitary transcriptome. Targeted sequencing of two candidate genes, SLC20A1 and SLC15A4, of the solute carrier membrane transport protein family in 200 additional patients demonstrated two further variants predicted as damaging. We also found combinations of de novo (SLC20A1/SLC15A4) and transmitted variants (GLI2/LHX3) in the same individuals, leading to the full-blown CPHD phenotype.ConclusionThese data expand the pituitary target genes repertoire for diagnostics and further functional studies. Exome sequencing has identified a combination of rare variants in different genes that might explain incomplete penetrance in CPHD.Genetics in Medicine advance online publication, 26 October 2017; doi:10.1038/gim.2017.165.

A public platform for the verification of the phenotypic effect of candidate genes for resistance to aflatoxin accumulation and Aspergillus flavus infection in maize

USDA-ARS?s Scientific Manuscript database

A public candidate gene testing pipeline for resistance to aflatoxin accumulation or Aspergillus flavus infection in maize is presented here. The pipeline consists of steps for identifying, testing, and verifying the association of any maize gene sequence with resistance under field conditions. Reso...

SNP discovery in candidate adaptive genes using exon capture in a free-ranging alpine ungulate

Treesearch

Gretchen H. Roffler; Stephen J. Amish; Seth Smith; Ted Cosart; Marty Kardos; Michael K. Schwartz; Gordon Luikart

2016-01-01

Identification of genes underlying genomic signatures of natural selection is key to understanding adaptation to local conditions. We used targeted resequencing to identify SNP markers in 5321 candidate adaptive genes associated with known immunological, metabolic and growth functions in ovids and other ungulates. We selectively targeted 8161 exons in protein-coding...

Implementing targeted region capture sequencing for the clinical detection of Alagille syndrome: An efficient and cost‑effective method.

PubMed

Huang, Tianhong; Yang, Guilin; Dang, Xiao; Ao, Feijian; Li, Jiankang; He, Yizhou; Tang, Qiyuan; He, Qing

2017-11-01

Alagille syndrome (AGS) is a highly variable, autosomal dominant disease that affects multiple structures including the liver, heart, eyes, bones and face. Targeted region capture sequencing focuses on a panel of known pathogenic genes and provides a rapid, cost‑effective and accurate method for molecular diagnosis. In a Chinese family, this method was used on the proband and Sanger sequencing was applied to validate the candidate mutation. A de novo heterozygous mutation (c.3254_3255insT p.Leu1085PhefsX24) of the jagged 1 gene was identified as the potential disease‑causing gene mutation. In conclusion, the present study suggested that target region capture sequencing is an efficient, reliable and accurate approach for the clinical diagnosis of AGS. Furthermore, these results expand on the understanding of the pathogenesis of AGS.

Identification of Candidate Genes Involved in the Salt Tolerance of Date Palm (Phoenix dactylifera L.) Based on a Yeast Functional Bioassay.

PubMed

Patankar, Himanshu V; Al-Harrasi, Ibtisam; Al-Yahyai, Rashid; Yaish, Mahmoud W

2018-06-01

Although date palm is a relatively salt-tolerant plant, the molecular basis of this tolerance is complex and poorly understood. Therefore, this study aimed to identify the genes involved in salinity tolerance using a basic yeast functional bioassay. To achieve this, a date palm cDNA library was overexpressed in Saccharomyces cerevisiae cells. The expression levels of selected genes that make yeast cells tolerant to salt were subsequently validated in the leaf and root tissues of date palm seedlings using a quantitative PCR method. About 6000 yeast transformant cells were replica printed and screened on a synthetic minimal medium containing 1.0 M of NaCl. The screening results showed the presence of 62 salt-tolerant transformant colonies. Sequence analysis of the recombinant yeast plasmids revealed the presence of a group of genes with potential salt-tolerance functions, such as aquaporins (PIP), serine/threonine protein kinases (STKs), ethylene-responsive transcription factor 1 (ERF1), and peroxidases (PRX). The expression pattern of the selected genes endorsed the hypothesis that these genes may be involved in salinity tolerance, as they showed a significant (p < 0.05) overexpression trend in both the leaf and root tissues in response to salinity. The genes identified in this project are suitable candidates for the further functional characterization of date palms.

A genomic scan for selection reveals candidates for genes involved in the evolution of cultivated sunflower (Helianthus annuus).

PubMed

Chapman, Mark A; Pashley, Catherine H; Wenzler, Jessica; Hvala, John; Tang, Shunxue; Knapp, Steven J; Burke, John M

2008-11-01

Genomic scans for selection are a useful tool for identifying genes underlying phenotypic transitions. In this article, we describe the results of a genome scan designed to identify candidates for genes targeted by selection during the evolution of cultivated sunflower. This work involved screening 492 loci derived from ESTs on a large panel of wild, primitive (i.e., landrace), and improved sunflower (Helianthus annuus) lines. This sampling strategy allowed us to identify candidates for selectively important genes and investigate the likely timing of selection. Thirty-six genes showed evidence of selection during either domestication or improvement based on multiple criteria, and a sequence-based test of selection on a subset of these loci confirmed this result. In view of what is known about the structure of linkage disequilibrium across the sunflower genome, these genes are themselves likely to have been targeted by selection, rather than being merely linked to the actual targets. While the selection candidates showed a broad range of putative functions, they were enriched for genes involved in amino acid synthesis and protein catabolism. Given that a similar pattern has been detected in maize (Zea mays), this finding suggests that selection on amino acid composition may be a general feature of the evolution of crop plants. In terms of genomic locations, the selection candidates were significantly clustered near quantitative trait loci (QTL) that contribute to phenotypic differences between wild and cultivated sunflower, and specific instances of QTL colocalization provide some clues as to the roles that these genes may have played during sunflower evolution.

A cross-species analysis method to analyze animal models' similarity to human's disease state

PubMed Central

2012-01-01

Background Animal models are indispensable tools in studying the cause of human diseases and searching for the treatments. The scientific value of an animal model depends on the accurate mimicry of human diseases. The primary goal of the current study was to develop a cross-species method by using the animal models' expression data to evaluate the similarity to human diseases' and assess drug molecules' efficiency in drug research. Therefore, we hoped to reveal that it is feasible and useful to compare gene expression profiles across species in the studies of pathology, toxicology, drug repositioning, and drug action mechanism. Results We developed a cross-species analysis method to analyze animal models' similarity to human diseases and effectiveness in drug research by utilizing the existing animal gene expression data in the public database, and mined some meaningful information to help drug research, such as potential drug candidates, possible drug repositioning, side effects and analysis in pharmacology. New animal models could be evaluated by our method before they are used in drug discovery. We applied the method to several cases of known animal model expression profiles and obtained some useful information to help drug research. We found that trichostatin A and some other HDACs could have very similar response across cell lines and species at gene expression level. Mouse hypoxia model could accurately mimic the human hypoxia, while mouse diabetes drug model might have some limitation. The transgenic mouse of Alzheimer was a useful model and we deeply analyzed the biological mechanisms of some drugs in this case. In addition, all the cases could provide some ideas for drug discovery and drug repositioning. Conclusions We developed a new cross-species gene expression module comparison method to use animal models' expression data to analyse the effectiveness of animal models in drug research. Moreover, through data integration, our method could be applied for drug research, such as potential drug candidates, possible drug repositioning, side effects and information about pharmacology. PMID:23282076

A cross-species analysis method to analyze animal models' similarity to human's disease state.

PubMed

Yu, Shuhao; Zheng, Lulu; Li, Yun; Li, Chunyan; Ma, Chenchen; Li, Yixue; Li, Xuan; Hao, Pei

2012-01-01

Animal models are indispensable tools in studying the cause of human diseases and searching for the treatments. The scientific value of an animal model depends on the accurate mimicry of human diseases. The primary goal of the current study was to develop a cross-species method by using the animal models' expression data to evaluate the similarity to human diseases' and assess drug molecules' efficiency in drug research. Therefore, we hoped to reveal that it is feasible and useful to compare gene expression profiles across species in the studies of pathology, toxicology, drug repositioning, and drug action mechanism. We developed a cross-species analysis method to analyze animal models' similarity to human diseases and effectiveness in drug research by utilizing the existing animal gene expression data in the public database, and mined some meaningful information to help drug research, such as potential drug candidates, possible drug repositioning, side effects and analysis in pharmacology. New animal models could be evaluated by our method before they are used in drug discovery. We applied the method to several cases of known animal model expression profiles and obtained some useful information to help drug research. We found that trichostatin A and some other HDACs could have very similar response across cell lines and species at gene expression level. Mouse hypoxia model could accurately mimic the human hypoxia, while mouse diabetes drug model might have some limitation. The transgenic mouse of Alzheimer was a useful model and we deeply analyzed the biological mechanisms of some drugs in this case. In addition, all the cases could provide some ideas for drug discovery and drug repositioning. We developed a new cross-species gene expression module comparison method to use animal models' expression data to analyse the effectiveness of animal models in drug research. Moreover, through data integration, our method could be applied for drug research, such as potential drug candidates, possible drug repositioning, side effects and information about pharmacology.

A priori and a posteriori approaches for finding genes of evolutionary interest in non-model species: osmoregulatory genes in the kidney transcriptome of the desert rodent Dipodomys spectabilis (banner-tailed kangaroo rat).

PubMed

Marra, Nicholas J; Eo, Soo Hyung; Hale, Matthew C; Waser, Peter M; DeWoody, J Andrew

2012-12-01

One common goal in evolutionary biology is the identification of genes underlying adaptive traits of evolutionary interest. Recently next-generation sequencing techniques have greatly facilitated such evolutionary studies in species otherwise depauperate of genomic resources. Kangaroo rats (Dipodomys sp.) serve as exemplars of adaptation in that they inhabit extremely arid environments, yet require no drinking water because of ultra-efficient kidney function and osmoregulation. As a basis for identifying water conservation genes in kangaroo rats, we conducted a priori bioinformatics searches in model rodents (Mus musculus and Rattus norvegicus) to identify candidate genes with known or suspected osmoregulatory function. We then obtained 446,758 reads via 454 pyrosequencing to characterize genes expressed in the kidney of banner-tailed kangaroo rats (Dipodomys spectabilis). We also determined candidates a posteriori by identifying genes that were overexpressed in the kidney. The kangaroo rat sequences revealed nine different a priori candidate genes predicted from our Mus and Rattus searches, as well as 32 a posteriori candidate genes that were overexpressed in kidney. Mutations in two of these genes, Slc12a1 and Slc12a3, cause human renal diseases that result in the inability to concentrate urine. These genes are likely key determinants of physiological water conservation in desert rodents. Copyright © 2012 Elsevier Inc. All rights reserved.

Reference genes for measuring mRNA expression.

PubMed

Dundas, Jitesh; Ling, Maurice

2012-12-01

The aim of this review is to find answers to some of the questions surrounding reference genes and their reliability for quantitative experiments. Reference genes are assumed to be at a constant expression level, over a range of conditions such as temperature. These genes, such as GADPH and beta-actin, are used extensively for gene expression studies using techniques like quantitative PCR. There have been several studies carried out on identifying reference genes. However, a lot of evidence indicates issues to the general suitability of these genes. Recent studies had shown that different factors, including the environment and methods, play an important role in changing the expression levels of the reference genes. Thus, we conclude that there is no reference gene that can deemed suitable for all the experimental conditions. In addition, we believe that every experiment will require the scientific evaluation and selection of the best candidate gene for use as a reference gene to obtain reliable scientific results.

Genomic analysis of human lung fibroblasts exposed to vanadium pentoxide to identify candidate genes for occupational bronchitis

PubMed Central

Ingram, Jennifer L; Antao-Menezes, Aurita; Turpin, Elizabeth A; Wallace, Duncan G; Mangum, James B; Pluta, Linda J; Thomas, Russell S; Bonner, James C

2007-01-01

Background Exposure to vanadium pentoxide (V2O5) is a cause of occupational bronchitis. We evaluated gene expression profiles in cultured human lung fibroblasts exposed to V2O5 in vitro in order to identify candidate genes that could play a role in inflammation, fibrosis, and repair during the pathogenesis of V2O5-induced bronchitis. Methods Normal human lung fibroblasts were exposed to V2O5 in a time course experiment. Gene expression was measured at various time points over a 24 hr period using the Affymetrix Human Genome U133A 2.0 Array. Selected genes that were significantly changed in the microarray experiment were validated by RT-PCR. Results V2O5 altered more than 1,400 genes, of which ~300 were induced while >1,100 genes were suppressed. Gene ontology categories (GO) categories unique to induced genes included inflammatory response and immune response, while GO catogories unique to suppressed genes included ubiquitin cycle and cell cycle. A dozen genes were validated by RT-PCR, including growth factors (HBEGF, VEGF, CTGF), chemokines (IL8, CXCL9, CXCL10), oxidative stress response genes (SOD2, PIPOX, OXR1), and DNA-binding proteins (GAS1, STAT1). Conclusion Our study identified a variety of genes that could play pivotal roles in inflammation, fibrosis and repair during V2O5-induced bronchitis. The induction of genes that mediate inflammation and immune responses, as well as suppression of genes involved in growth arrest appear to be important to the lung fibrotic reaction to V2O5. PMID:17459161

Association analysis of single nucleotide polymorphisms in candidate genes with root traits in maize (Zea mays L.) seedlings.

PubMed

Kumar, Bharath; Abdel-Ghani, Adel H; Pace, Jordon; Reyes-Matamoros, Jenaro; Hochholdinger, Frank; Lübberstedt, Thomas

2014-07-01

Several genes involved in maize root development have been isolated. Identification of SNPs associated with root traits would enable the selection of maize lines with better root architecture that might help to improve N uptake, and consequently plant growth particularly under N deficient conditions. In the present study, an association study (AS) panel consisting of 74 maize inbred lines was screened for seedling root traits in 6, 10, and 14-day-old seedlings. Allele re-sequencing of candidate root genes Rtcl, Rth3, Rum1, and Rul1 was also carried out in the same AS panel lines. All four candidate genes displayed different levels of nucleotide diversity, haplotype diversity and linkage disequilibrium. Gene based association analyses were carried out between individual polymorphisms in candidate genes, and root traits measured in 6, 10, and 14-day-old maize seedlings. Association analyses revealed several polymorphisms within the Rtcl, Rth3, Rum1, and Rul1 genes associated with seedling root traits. Several nucleotide polymorphisms in Rtcl, Rth3, Rum1, and Rul1 were significantly (P<0.05) associated with seedling root traits in maize suggesting that all four tested genes are involved in the maize root development. Thus considerable allelic variation present in these root genes can be exploited for improving maize root characteristics. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Rapid Communication: MiR-92a as a housekeeping gene for analysis of bovine mastitis-related microRNA in milk.

PubMed

Lai, Y C; Fujikawa, T; Ando, T; Kitahara, G; Koiwa, M; Kubota, C; Miura, N

2017-06-01

Our aim was to identify a suitable microRNA housekeeping gene for real-time PCR analysis of bovine mastitis-related microRNA in milk. We identified , , and as housekeeping gene candidates on the basis of previous Solexa sequencing results. Threshold cycle (CT) values for , , and did not differ between milk from control cows and milk from mastitis-affected cows. NormFinder software identified as the most stable single housekeeping gene. We evaluated the suitability of the housekeeping gene candidates by using them to assess expression levels of the inflammation-related gene . Regardless of the housekeeping gene candidates used for normalization, relative expression levels of were significantly higher in mastitis-affected samples than in control samples. However, of all the housekeeping genes and gene combinations investigated, normalization with alone generated the difference in relative expression between mastitis-affected and control samples with the highest significance. These results suggest that is suitable for use as a housekeeping gene for analysis of bovine mastitis-related microRNA in milk.

A network-based method for the identification of putative genes related to infertility.

PubMed

Wang, ShaoPeng; Huang, GuoHua; Hu, Qinghua; Zou, Quan

2016-11-01

Infertility has become one of the major health problems worldwide, with its incidence having risen markedly in recent decades. There is an urgent need to investigate the pathological mechanisms behind infertility and to design effective treatments. However, this is made difficult by the fact that various biological factors have been identified to be related to infertility, including genetic factors. A network-based method was established to identify new genes potentially related to infertility. A network constructed using human protein-protein interactions based on previously validated infertility-related genes enabled the identification of some novel candidate genes. These genes were then filtered by a permutation test and their functional and structural associations with infertility-related genes. Our method identified 23 novel genes, which have strong functional and structural associations with previously validated infertility-related genes. Substantial evidence indicates that the identified genes are strongly related to dysfunction of the four main biological processes of fertility: reproductive development and physiology, gametogenesis, meiosis and recombination, and hormone regulation. The newly discovered genes may provide new directions for investigating infertility. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang. Copyright © 2016 Elsevier B.V. All rights reserved.

DNA Barcoding for Efficient Species- and Pathovar-Level Identification of the Quarantine Plant Pathogen Xanthomonas

PubMed Central

Tian, Qian; Zhao, Wenjun; Lu, Songyu; Zhu, Shuifang; Li, Shidong

2016-01-01

Genus Xanthomonas comprises many economically important plant pathogens that affect a wide range of hosts. Indeed, fourteen Xanthomonas species/pathovars have been regarded as official quarantine bacteria for imports in China. To date, however, a rapid and accurate method capable of identifying all of the quarantine species/pathovars has yet to be developed. In this study, we therefore evaluated the capacity of DNA barcoding as a digital identification method for discriminating quarantine species/pathovars of Xanthomonas. For these analyses, 327 isolates, representing 45 Xanthomonas species/pathovars, as well as five additional species/pathovars from GenBank (50 species/pathovars total), were utilized to test the efficacy of four DNA barcode candidate genes (16S rRNA gene, cpn60, gyrB, and avrBs2). Of these candidate genes, cpn60 displayed the highest rate of PCR amplification and sequencing success. The tree-building (Neighbor-joining), ‘best close match’, and barcode gap methods were subsequently employed to assess the species- and pathovar-level resolution of each gene. Notably, all isolates of each quarantine species/pathovars formed a monophyletic group in the neighbor-joining tree constructed using the cpn60 sequences. Moreover, cpn60 also demonstrated the most satisfactory results in both barcoding gap analysis and the ‘best close match’ test. Thus, compared with the other markers tested, cpn60 proved to be a powerful DNA barcode, providing a reliable and effective means for the species- and pathovar-level identification of the quarantine plant pathogen Xanthomonas. PMID:27861494

Transactional Database Transformation and Its Application in Prioritizing Human Disease Genes

PubMed Central

Xiang, Yang; Payne, Philip R.O.; Huang, Kun

2013-01-01

Binary (0,1) matrices, commonly known as transactional databases, can represent many application data, including gene-phenotype data where “1” represents a confirmed gene-phenotype relation and “0” represents an unknown relation. It is natural to ask what information is hidden behind these “0”s and “1”s. Unfortunately, recent matrix completion methods, though very effective in many cases, are less likely to infer something interesting from these (0,1)-matrices. To answer this challenge, we propose IndEvi, a very succinct and effective algorithm to perform independent-evidence-based transactional database transformation. Each entry of a (0,1)-matrix is evaluated by “independent evidence” (maximal supporting patterns) extracted from the whole matrix for this entry. The value of an entry, regardless of its value as 0 or 1, has completely no effect for its independent evidence. The experiment on a gene-phenotype database shows that our method is highly promising in ranking candidate genes and predicting unknown disease genes. PMID:21422495

Generation of novel pharmacogenomic candidates in the response to methotrexate in juvenile idiopathic arthritis: correlation between gene expression and genotype

PubMed Central

Moncrieffe, Halima; Hinks, Anne; Ursu, Simona; Kassoumeri, Laura; Etheridge, Angela; Hubank, Mike; Martin, Paul; Weiler, Tracey; Glass, David N; Thompson, Susan D.; Thomson, Wendy; Wedderburn, Lucy R

2010-01-01

Objectives Little is known about mechanisms of efficacy of methotrexate (MTX) in childhood arthritis, or genetic influences upon response to MTX. The aims of this study were to use gene expression profiling to identify novel pathways/genes altered by MTX and then investigate these genes for genotype associations with response to MTX treatment. Methods Gene expression profiling before and after MTX treatment was performed on 11 children with juvenile idiopathic arthritis (JIA) treated with MTX, in whom response at 6 months of treatment was defined. Genes showing the most differential gene expression after treatment were selected for SNP genotyping. Genotype frequencies were compared between non-responders and responders (ACR-Ped70). An independent cohort was available for validation. Results Gene expression profiling before and after MTX treatment revealed 1222 differentially expressed probes sets (fold change >1.7, p< 0.05) and 1065 when restricted to full responder cases only. Six highly differentially expressed genes were analysed for genetic association to response to MTX. Three SNPs in the SLC16A7 gene showed significant association with MTX response. One SNP showed validated association in an independent cohort. Conclusions This study is the first, to our knowledge, to evaluate gene expression profiles in children with JIA before and after MTX, and to analyse genetic variation in differentially expressed genes. We have identified a gene which may contribute to genetic variability in MTX response in JIA, and established as proof of principle that genes which are differentially expressed at mRNA level after drug administration may also be good candidates for genetic analysis. PMID:20827233

Systematic Prioritization and Integrative Analysis of Copy Number Variations in Schizophrenia Reveal Key Schizophrenia Susceptibility Genes

PubMed Central

Luo, Xiongjian; Huang, Liang; Han, Leng; Luo, Zhenwu; Hu, Fang; Tieu, Roger; Gan, Lin

2014-01-01

Schizophrenia is a common mental disorder with high heritability and strong genetic heterogeneity. Common disease-common variants hypothesis predicts that schizophrenia is attributable in part to common genetic variants. However, recent studies have clearly demonstrated that copy number variations (CNVs) also play pivotal roles in schizophrenia susceptibility and explain a proportion of missing heritability. Though numerous CNVs have been identified, many of the regions affected by CNVs show poor overlapping among different studies, and it is not known whether the genes disrupted by CNVs contribute to the risk of schizophrenia. By using cumulative scoring, we systematically prioritized the genes affected by CNVs in schizophrenia. We identified 8 top genes that are frequently disrupted by CNVs, including NRXN1, CHRNA7, BCL9, CYFIP1, GJA8, NDE1, SNAP29, and GJA5. Integration of genes affected by CNVs with known schizophrenia susceptibility genes (from previous genetic linkage and association studies) reveals that many genes disrupted by CNVs are also associated with schizophrenia. Further protein-protein interaction (PPI) analysis indicates that protein products of genes affected by CNVs frequently interact with known schizophrenia-associated proteins. Finally, systematic integration of CNVs prioritization data with genetic association and PPI data identifies key schizophrenia candidate genes. Our results provide a global overview of genes impacted by CNVs in schizophrenia and reveal a densely interconnected molecular network of de novo CNVs in schizophrenia. Though the prioritized top genes represent promising schizophrenia risk genes, further work with different prioritization methods and independent samples is needed to confirm these findings. Nevertheless, the identified key candidate genes may have important roles in the pathogenesis of schizophrenia, and further functional characterization of these genes may provide pivotal targets for future therapeutics and diagnostics. PMID:24664977

Evaluation and Validation of Reference Genes for qRT-PCR Normalization in Frankliniella occidentalis (Thysanoptera:Thripidae)

PubMed Central

Zheng, Yu-Tao; Li, Hong-Bo; Lu, Ming-Xing; Du, Yu-Zhou

2014-01-01

Quantitative real time PCR (qRT-PCR) has emerged as a reliable and reproducible technique for studying gene expression analysis. For accurate results, the normalization of data with reference genes is particularly essential. Once the transcriptome sequencing of Frankliniella occidentalis was completed, numerous unigenes were identified and annotated. Unfortunately, there are no studies on the stability of reference genes used in F. occidentalis. In this work, seven candidate reference genes, including actin, 18S rRNA, H3, tubulin, GAPDH, EF-1 and RPL32, were evaluated for their suitability as normalization genes under different experimental conditions using the statistical software programs BestKeeper, geNorm, Normfinder and the comparative ΔCt method. Because the rankings of the reference genes provided by each of the four programs were different, we chose a user-friendly web-based comprehensive tool RefFinder to get the final ranking. The result demonstrated that EF-1 and RPL32 displayed the most stable expression in different developmental stages; RPL32 and GAPDH showed the most stable expression at high temperatures, while 18S and EF-1 exhibited the most stable expression at low temperatures. In this study, we validated the suitable reference genes in F. occidentalis for gene expression profiling under different experimental conditions. The choice of internal standard is very important in the normalization of the target gene expression levels, thus validating and selecting the best genes will help improve the quality of gene expression data of F. occidentalis. What is more, these validated reference genes could serve as the basis for the selection of candidate reference genes in other insects. PMID:25356721

Evaluation and validation of reference genes for qRT-PCR normalization in Frankliniella occidentalis (Thysanoptera: Thripidae).

PubMed

Zheng, Yu-Tao; Li, Hong-Bo; Lu, Ming-Xing; Du, Yu-Zhou

2014-01-01

Quantitative real time PCR (qRT-PCR) has emerged as a reliable and reproducible technique for studying gene expression analysis. For accurate results, the normalization of data with reference genes is particularly essential. Once the transcriptome sequencing of Frankliniella occidentalis was completed, numerous unigenes were identified and annotated. Unfortunately, there are no studies on the stability of reference genes used in F. occidentalis. In this work, seven candidate reference genes, including actin, 18S rRNA, H3, tubulin, GAPDH, EF-1 and RPL32, were evaluated for their suitability as normalization genes under different experimental conditions using the statistical software programs BestKeeper, geNorm, Normfinder and the comparative ΔCt method. Because the rankings of the reference genes provided by each of the four programs were different, we chose a user-friendly web-based comprehensive tool RefFinder to get the final ranking. The result demonstrated that EF-1 and RPL32 displayed the most stable expression in different developmental stages; RPL32 and GAPDH showed the most stable expression at high temperatures, while 18S and EF-1 exhibited the most stable expression at low temperatures. In this study, we validated the suitable reference genes in F. occidentalis for gene expression profiling under different experimental conditions. The choice of internal standard is very important in the normalization of the target gene expression levels, thus validating and selecting the best genes will help improve the quality of gene expression data of F. occidentalis. What is more, these validated reference genes could serve as the basis for the selection of candidate reference genes in other insects.

Children’s Hospital of Pittsburgh and Diabetes Institute of the Walter Reed Health Care System Genetic Screening in Diabetes: Candidate Gene Analysis for Diabetic Retinopathy

DTIC Science & Technology

2010-05-01

Screening in Diabetes : Candidate Gene Analysis for Diabetic Retinopathy PRINCIPAL INVESTIGATOR: Robert A. Vigersky, COL MC CONTRACTING ORGANIZATION... Diabetes Institute of the Walter Reed Health Care System Genetic Screening in Diabetes : Candidate Gene Analysis for Diabetic Retinopathy 5c. PROGRAM... diabetic  neuropathy, and  diabetic   retinopathy .  This was an observational study in which the investigators obtained DNA samples from the blood of

Gene Expression Profiling of Gastric Cancer

PubMed Central

Marimuthu, Arivusudar; Jacob, Harrys K.C.; Jakharia, Aniruddha; Subbannayya, Yashwanth; Keerthikumar, Shivakumar; Kashyap, Manoj Kumar; Goel, Renu; Balakrishnan, Lavanya; Dwivedi, Sutopa; Pathare, Swapnali; Dikshit, Jyoti Bajpai; Maharudraiah, Jagadeesha; Singh, Sujay; Sameer Kumar, Ghantasala S; Vijayakumar, M.; Veerendra Kumar, Kariyanakatte Veeraiah; Premalatha, Chennagiri Shrinivasamurthy; Tata, Pramila; Hariharan, Ramesh; Roa, Juan Carlos; Prasad, T.S.K; Chaerkady, Raghothama; Kumar, Rekha Vijay; Pandey, Akhilesh

2015-01-01

Gastric cancer is the second leading cause of cancer death worldwide, both in men and women. A genomewide gene expression analysis was carried out to identify differentially expressed genes in gastric adenocarcinoma tissues as compared to adjacent normal tissues. We used Agilent’s whole human genome oligonucleotide microarray platform representing ~41,000 genes to carry out gene expression analysis. Two-color microarray analysis was employed to directly compare the expression of genes between tumor and normal tissues. Through this approach, we identified several previously known candidate genes along with a number of novel candidate genes in gastric cancer. Testican-1 (SPOCK1) was one of the novel molecules that was 10-fold upregulated in tumors. Using tissue microarrays, we validated the expression of testican-1 by immunohistochemical staining. It was overexpressed in 56% (160/282) of the cases tested. Pathway analysis led to the identification of several networks in which SPOCK1 was among the topmost networks of interacting genes. By gene enrichment analysis, we identified several genes involved in cell adhesion and cell proliferation to be significantly upregulated while those corresponding to metabolic pathways were significantly downregulated. The differentially expressed genes identified in this study are candidate biomarkers for gastric adenoacarcinoma. PMID:27030788

Identification of possible genetic polymorphisms involved in cancer cachexia: a systematic review.

PubMed

Tan, Benjamin H L; Ross, James A; Kaasa, Stein; Skorpen, Frank; Fearon, Kenneth C H

2011-04-01

Cancer cachexia is a polygenic and complex syndrome. Genetic variations in regulation of the inflammatory response, muscle and fat metabolic pathways, and pathways in appetite regulation are likely to contribute to the susceptibility or resistance to developing cancer cachexia. A systematic search of Medline and EmBase databases, covering 1986-2008 was performed for potential candidate genes/genetic polymorphisms relating to cancer cachexia. Related genes were then identified using pathway functional analysis software. All candidate genes were reviewed for functional polymorphisms or clinically significant polymorphisms associated with cachexia using the OMIM and GeneRIF databases. Genes with variants which had functional or clinical associations with cachexia and replicated in at least one study were entered into pathway analysis software to reveal possible network associations between genes. A total of 184 polymorphisms with functional or clinical relevance to cancer cachexia were identified in 92 candidate genes. Of these, 42 polymorphisms (in 33 genes) were replicated in more than one study with 13 polymorphisms found to influence two or more hallmarks of cachexia (i.e. inflammation, loss of fat mass and/or lean mass and reduced survival). Thirty-three genes were found to be significantly interconnected in two major networks with four genes (ADIPOQ, IL6, NFKB1 and TLR4) interlinking both networks. Selection of candidate genes and polymorphisms is a key element of multigene study design. The present study provides an initial framework to select genes/polymorphisms for further study in cancer cachexia, and to develop their potential as susceptibility biomarkers of developing cachexia.

Transcription map of Xq27: candidates for several X-linked diseases.

PubMed

Zucchi, I; Jones, J; Affer, M; Montagna, C; Redolfi, E; Susani, L; Vezzoni, P; Parvari, R; Schlessinger, D; Whyte, M P; Mumm, S

1999-04-15

Human Xq27 contains candidate regions for several disorders, yet is predicted to be a gene-poor cytogenetic band. We have developed a transcription map for the entire cytogenetic band to facilitate the identification of the relatively small number of expected candidate genes. Two approaches were taken to identify genes: (1) a group of 64 unique STSs that were generated during the physical mapping of the region were used in RT-PCR with RNA from human adult and fetal brain and (2) ESTs that have been broadly mapped to this region of the chromosome were finely mapped using a high-resolution yeast artificial chromosome contig. This combined approach identified four distinct regions of transcriptional activity within the Xq27 band. Among them is a region at the centromeric boundary that contains candidate regions for several rare developmental disorders (X-linked recessive hypoparathyroidism, thoracoabdominal syndrome, albinism-deafness syndrome, and Borjeson-Forssman-Lehman syndrome). Two transcriptionally active regions were identified in the center of Xq27 and include candidate regions for X-linked mental retardation syndrome 6, X-linked progressive cone dystrophy, X-linked retinitis pigmentosa 24, and a prostate cancer susceptibility locus. The fourth region of transcriptional activity encompasses the FMR1 (FRAXA) and FMR2 (FRAXE) genes. The analysis thus suggests clustered transcription in Xq27 and provides candidates for several heritable disorders for which the causative genes have not yet been found. Copyright 1999 Academic Press.

PCAN: phenotype consensus analysis to support disease-gene association.

PubMed

Godard, Patrice; Page, Matthew

2016-12-07

Bridging genotype and phenotype is a fundamental biomedical challenge that underlies more effective target discovery and patient-tailored therapy. Approaches that can flexibly and intuitively, integrate known gene-phenotype associations in the context of molecular signaling networks are vital to effectively prioritize and biologically interpret genes underlying disease traits of interest. We describe Phenotype Consensus Analysis (PCAN); a method to assess the consensus semantic similarity of phenotypes in a candidate gene's signaling neighborhood. We demonstrate that significant phenotype consensus (p < 0.05) is observable for ~67% of 4,549 OMIM disease-gene associations, using a combination of high quality String interactions + Metabase pathways and use Joubert Syndrome to demonstrate the ease with which a significant result can be interrogated to highlight discriminatory traits linked to mechanistically related genes. We advocate phenotype consensus as an intuitive and versatile method to aid disease-gene association, which naturally lends itself to the mechanistic deconvolution of diverse phenotypes. We provide PCAN to the community as an R package ( http://bioconductor.org/packages/PCAN/ ) to allow flexible configuration, extension and standalone use or integration to supplement existing gene prioritization workflows.

Identification of Regulatory Genes Implicated in Continuous Flowering of Longan (Dimocarpus longan L.)

PubMed Central

Jia, Tianqi; Wei, Danfeng; Meng, Shan; Allan, Andrew C.; Zeng, Lihui

2014-01-01

Longan (Dimocarpus longan L.) is a tropical/subtropical fruit tree of significant economic importance in Southeast Asia. However, a lack of transcriptomic and genomic information hinders research on longan traits, such as the control of flowering. In this study, high-throughput RNA sequencing (RNA-Seq) was used to investigate differentially expressed genes between a unique longan cultivar ‘Sijimi’(S) which flowers throughout the year and a more typical cultivar ‘Lidongben’(L) which flowers only once in the season, with the aim of identifying candidate genes associated with continuous flowering. 36,527 and 40,982 unigenes were obtained by de novo assembly of the clean reads from cDNA libraries of L and S cultivars. Additionally 40,513 unigenes were assembled from combined reads of these libraries. A total of 32,475 unigenes were annotated by BLAST search to NCBI non-redundant protein (NR), Swiss-Prot, Clusters of Orthologous Groups (COGs) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Of these, almost fifteen thousand unigenes were identified as significantly differentially expressed genes (DEGs) by using Reads Per kb per Million reads (RPKM) method. A total of 6,415 DEGs were mapped to 128 KEGG pathways, and 8,743 DEGs were assigned to 54 Gene Ontology categories. After blasting the DEGs to public sequence databases, 539 potential flowering-related DEGs were identified. In addition, 107 flowering-time genes were identified in longan, their expression levels between two longan samples were compared by RPKM method, of which the expression levels of 15 were confirmed by real-time quantitative PCR. Our results suggest longan homologues of SHORT VEGETATIVE PHASE (SVP), GIGANTEA (GI), F-BOX 1 (FKF1) and EARLY FLOWERING 4 (ELF4) may be involved this flowering trait and ELF4 may be a key gene. The identification of candidate genes related to continuous flowering will provide new insight into the molecular process of regulating flowering time in woody plants. PMID:25479005

Genetic risk factors of systemic lupus erythematosus in the Malaysian population: a minireview.

PubMed

Chai, Hwa Chia; Phipps, Maude Elvira; Chua, Kek Heng

2012-01-01

SLE is an autoimmune disease that is not uncommon in Malaysia. In contrast to Malays and Indians, the Chinese seem to be most affected. SLE is characterized by deficiency of body's immune response that leads to production of autoantibodies and failure of immune complex clearance. This minireview attempts to summarize the association of several candidate genes with risk for SLE in the Malaysian population and discuss the genetic heterogeneity that exists locally in Asians and in comparison with SLE in Caucasians. Several groups of researchers have been actively investigating genes that are associated with SLE susceptibility in the Malaysian population by screening possible reported candidate genes across the SLE patients and healthy controls. These candidate genes include MHC genes and genes encoding complement components, TNF, FcγR, T-cell receptors, and interleukins. However, most of the polymorphisms investigated in these genes did not show significant associations with susceptibility to SLE in the Malaysian scenario, except for those occurring in MHC genes and genes coding for TNF-α, IL-1β, IL-1RN, and IL-6.

Genetic Risk Factors of Systemic Lupus Erythematosus in the Malaysian Population: A Minireview

PubMed Central

Chai, Hwa Chia; Phipps, Maude Elvira; Chua, Kek Heng

2012-01-01

SLE is an autoimmune disease that is not uncommon in Malaysia. In contrast to Malays and Indians, the Chinese seem to be most affected. SLE is characterized by deficiency of body's immune response that leads to production of autoantibodies and failure of immune complex clearance. This minireview attempts to summarize the association of several candidate genes with risk for SLE in the Malaysian population and discuss the genetic heterogeneity that exists locally in Asians and in comparison with SLE in Caucasians. Several groups of researchers have been actively investigating genes that are associated with SLE susceptibility in the Malaysian population by screening possible reported candidate genes across the SLE patients and healthy controls. These candidate genes include MHC genes and genes encoding complement components, TNF, FcγR, T-cell receptors, and interleukins. However, most of the polymorphisms investigated in these genes did not show significant associations with susceptibility to SLE in the Malaysian scenario, except for those occurring in MHC genes and genes coding for TNF-α, IL-1β, IL-1RN, and IL-6. PMID:21941582

Genomic analysis of Meckel–Gruber syndrome in Arabs reveals marked genetic heterogeneity and novel candidate genes

PubMed Central

Shaheen, Ranad; Faqeih, Eissa; Alshammari, Muneera J; Swaid, Abdulrahman; Al-Gazali, Lihadh; Mardawi, Elham; Ansari, Shinu; Sogaty, Sameera; Seidahmed, Mohammed Z; AlMotairi, Muhammed I; Farra, Chantal; Kurdi, Wesam; Al-Rasheed, Shatha; Alkuraya, Fowzan S

2013-01-01

Meckel–Gruber syndrome (MKS, OMIM #249000) is a multiple congenital malformation syndrome that represents the severe end of the ciliopathy phenotypic spectrum. Despite the relatively common occurrence of this syndrome among Arabs, little is known about its genetic architecture in this population. This is a series of 18 Arab families with MKS, who were evaluated clinically and studied using autozygome-guided mutation analysis and exome sequencing. We show that autozygome-guided candidate gene analysis identified the underlying mutation in the majority (n=12, 71%). Exome sequencing revealed a likely pathogenic mutation in three novel candidate MKS disease genes. These include C5orf42, Ellis–van-Creveld disease gene EVC2 and SEC8 (also known as EXOC4), which encodes an exocyst protein with an established role in ciliogenesis. This is the largest and most comprehensive genomic study on MKS in Arabs and the results, in addition to revealing genetic and allelic heterogeneity, suggest that previously reported disease genes and the novel candidates uncovered by this study account for the overwhelming majority of MKS patients in our population. PMID:23169490

Identification of candidate genes in Populus cell wall biosynthesis using text-mining, co-expression network and comparative genomics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Xiaohan; Ye, Chuyu; Bisaria, Anjali

2011-01-01

Populus is an important bioenergy crop for bioethanol production. A greater understanding of cell wall biosynthesis processes is critical in reducing biomass recalcitrance, a major hindrance in efficient generation of ethanol from lignocellulosic biomass. Here, we report the identification of candidate cell wall biosynthesis genes through the development and application of a novel bioinformatics pipeline. As a first step, via text-mining of PubMed publications, we obtained 121 Arabidopsis genes that had the experimental evidences supporting their involvement in cell wall biosynthesis or remodeling. The 121 genes were then used as bait genes to query an Arabidopsis co-expression database and additionalmore » genes were identified as neighbors of the bait genes in the network, increasing the number of genes to 548. The 548 Arabidopsis genes were then used to re-query the Arabidopsis co-expression database and re-construct a network that captured additional network neighbors, expanding to a total of 694 genes. The 694 Arabidopsis genes were computationally divided into 22 clusters. Queries of the Populus genome using the Arabidopsis genes revealed 817 Populus orthologs. Functional analysis of gene ontology and tissue-specific gene expression indicated that these Arabidopsis and Populus genes are high likelihood candidates for functional genomics in relation to cell wall biosynthesis.« less

Phenome-driven disease genetics prediction toward drug discovery

PubMed Central

Chen, Yang; Li, Li; Zhang, Guo-Qiang; Xu, Rong

2015-01-01

Motivation: Discerning genetic contributions to diseases not only enhances our understanding of disease mechanisms, but also leads to translational opportunities for drug discovery. Recent computational approaches incorporate disease phenotypic similarities to improve the prediction power of disease gene discovery. However, most current studies used only one data source of human disease phenotype. We present an innovative and generic strategy for combining multiple different data sources of human disease phenotype and predicting disease-associated genes from integrated phenotypic and genomic data. Results: To demonstrate our approach, we explored a new phenotype database from biomedical ontologies and constructed Disease Manifestation Network (DMN). We combined DMN with mimMiner, which was a widely used phenotype database in disease gene prediction studies. Our approach achieved significantly improved performance over a baseline method, which used only one phenotype data source. In the leave-one-out cross-validation and de novo gene prediction analysis, our approach achieved the area under the curves of 90.7% and 90.3%, which are significantly higher than 84.2% (P < e−4) and 81.3% (P < e−12) for the baseline approach. We further demonstrated that our predicted genes have the translational potential in drug discovery. We used Crohn’s disease as an example and ranked the candidate drugs based on the rank of drug targets. Our gene prediction approach prioritized druggable genes that are likely to be associated with Crohn’s disease pathogenesis, and our rank of candidate drugs successfully prioritized the Food and Drug Administration-approved drugs for Crohn’s disease. We also found literature evidence to support a number of drugs among the top 200 candidates. In summary, we demonstrated that a novel strategy combining unique disease phenotype data with system approaches can lead to rapid drug discovery. Availability and implementation: nlp.case.edu/public/data/DMN Contact: rxx@case.edu PMID:26072493

Drug Target Prediction and Repositioning Using an Integrated Network-Based Approach

PubMed Central

Emig, Dorothea; Ivliev, Alexander; Pustovalova, Olga; Lancashire, Lee; Bureeva, Svetlana; Nikolsky, Yuri; Bessarabova, Marina

2013-01-01

The discovery of novel drug targets is a significant challenge in drug development. Although the human genome comprises approximately 30,000 genes, proteins encoded by fewer than 400 are used as drug targets in the treatment of diseases. Therefore, novel drug targets are extremely valuable as the source for first in class drugs. On the other hand, many of the currently known drug targets are functionally pleiotropic and involved in multiple pathologies. Several of them are exploited for treating multiple diseases, which highlights the need for methods to reliably reposition drug targets to new indications. Network-based methods have been successfully applied to prioritize novel disease-associated genes. In recent years, several such algorithms have been developed, some focusing on local network properties only, and others taking the complete network topology into account. Common to all approaches is the understanding that novel disease-associated candidates are in close overall proximity to known disease genes. However, the relevance of these methods to the prediction of novel drug targets has not yet been assessed. Here, we present a network-based approach for the prediction of drug targets for a given disease. The method allows both repositioning drug targets known for other diseases to the given disease and the prediction of unexploited drug targets which are not used for treatment of any disease. Our approach takes as input a disease gene expression signature and a high-quality interaction network and outputs a prioritized list of drug targets. We demonstrate the high performance of our method and highlight the usefulness of the predictions in three case studies. We present novel drug targets for scleroderma and different types of cancer with their underlying biological processes. Furthermore, we demonstrate the ability of our method to identify non-suspected repositioning candidates using diabetes type 1 as an example. PMID:23593264

The Influence of Genetics on Cystic Fibrosis Phenotypes

PubMed Central

Knowles, Michael R.; Drumm, Mitchell

2012-01-01

Technological advances in genetics have made feasible and affordable large studies to identify genetic variants that cause or modify a trait. Genetic studies have been carried out to assess variants in candidate genes, as well as polymorphisms throughout the genome, for their associations with heritable clinical outcomes of cystic fibrosis (CF), such as lung disease, meconium ileus, and CF-related diabetes. The candidate gene approach has identified some predicted relationships, while genome-wide surveys have identified several genes that would not have been obvious disease-modifying candidates, such as a methionine sulfoxide transferase gene that influences intestinal obstruction, or a region on chromosome 11 proximate to genes encoding a transcription factor and an apoptosis controller that associates with lung function. These unforeseen associations thus provide novel insight into disease pathophysiology, as well as suggesting new therapeutic strategies for CF. PMID:23209180

Selection and validation of reference genes for quantitative gene expression analyses in various tissues and seeds at different developmental stages in Bixa orellana L.

PubMed

Moreira, Viviane S; Soares, Virgínia L F; Silva, Raner J S; Sousa, Aurizangela O; Otoni, Wagner C; Costa, Marcio G C

2018-05-01

Bixa orellana L., popularly known as annatto, produces several secondary metabolites of pharmaceutical and industrial interest, including bixin, whose molecular basis of biosynthesis remain to be determined. Gene expression analysis by quantitative real-time PCR (qPCR) is an important tool to advance such knowledge. However, correct interpretation of qPCR data requires the use of suitable reference genes in order to reduce experimental variations. In the present study, we have selected four different candidates for reference genes in B. orellana , coding for 40S ribosomal protein S9 (RPS9), histone H4 (H4), 60S ribosomal protein L38 (RPL38) and 18S ribosomal RNA (18SrRNA). Their expression stabilities in different tissues (e.g. flower buds, flowers, leaves and seeds at different developmental stages) were analyzed using five statistical tools (NormFinder, geNorm, BestKeeper, ΔCt method and RefFinder). The results indicated that RPL38 is the most stable gene in different tissues and stages of seed development and 18SrRNA is the most unstable among the analyzed genes. In order to validate the candidate reference genes, we have analyzed the relative expression of a target gene coding for carotenoid cleavage dioxygenase 1 (CCD1) using the stable RPL38 and the least stable gene, 18SrRNA , for normalization of the qPCR data. The results demonstrated significant differences in the interpretation of the CCD1 gene expression data, depending on the reference gene used, reinforcing the importance of the correct selection of reference genes for normalization.

Stocking impacts the expression of candidate genes and physiological condition in introgressed brook charr (Salvelinus fontinalis) populations

PubMed Central

Lamaze, Fabien C; Garant, Dany; Bernatchez, Louis

2013-01-01

Translocation of plants and animal populations between environments is one of the major forms of anthropogenic perturbation experienced by pristine populations, and consequently, human-mediated hybridization by stocking practices between wild and exogenous conspecifics is of increasing concern. In this study, we compared the expression of seven candidate genes involved in multifactorial traits and regulatory pathways for growth as a function of level of introgressive hybridization between wild and domestic brook charr to test the null hypothesis of no effect of introgression on wild fish. Our analyses revealed that the expression of two of the genes tested, cytochrome c oxidase VIIa and the growth hormone receptor isoform I, was positively correlated with the level of introgression. We also observed a positive relationship between the extent of introgression and physiological status quantified by the Fulton's condition index. The expression of other genes was influenced by other variables, including year of sampling (reflecting different thermal conditions), sampling method and lake of origin. This is the first demonstration in nature that introgression from stocked populations has an impact on the expression of genes playing a role in important biological functions that may be related with fitness in wild introgressed populations. PMID:23467764

Reference gene selection for quantitative reverse transcription-polymerase chain reaction normalization during in vitro adventitious rooting in Eucalyptus globulus Labill.

PubMed

de Almeida, Márcia R; Ruedell, Carolina M; Ricachenevsky, Felipe K; Sperotto, Raul A; Pasquali, Giancarlo; Fett-Neto, Arthur G

2010-09-20

Eucalyptus globulus and its hybrids are very important for the cellulose and paper industry mainly due to their low lignin content and frost resistance. However, rooting of cuttings of this species is recalcitrant and exogenous auxin application is often necessary for good root development. To date one of the most accurate methods available for gene expression analysis is quantitative reverse transcription-polymerase chain reaction (qPCR); however, reliable use of this technique requires reference genes for normalization. There is no single reference gene that can be regarded as universal for all experiments and biological materials. Thus, the identification of reliable reference genes must be done for every species and experimental approach. The present study aimed at identifying suitable control genes for normalization of gene expression associated with adventitious rooting in E. globulus microcuttings. By the use of two distinct algorithms, geNorm and NormFinder, we have assessed gene expression stability of eleven candidate reference genes in E. globulus: 18S, ACT2, EF2, EUC12, H2B, IDH, SAND, TIP41, TUA, UBI and 33380. The candidate reference genes were evaluated in microccuttings rooted in vitro, in presence or absence of auxin, along six time-points spanning the process of adventitious rooting. Overall, the stability profiles of these genes determined with each one of the algorithms were very similar. Slight differences were observed in the most stable pair of genes indicated by each program: IDH and SAND for geNorm, and H2B and TUA for NormFinder. Both programs identified UBI and 18S as the most variable genes. To validate these results and select the most suitable reference genes, the expression profile of the ARGONAUTE1 gene was evaluated in relation to the most stable candidate genes indicated by each algorithm. Our study showed that expression stability varied between putative reference genes tested in E. globulus. Based on the AGO1 relative expression profile obtained using the genes suggested by the algorithms, H2B and TUA were considered as the most suitable reference genes for expression studies in E. globulus adventitious rooting. UBI and 18S were unsuitable for use as controls in qPCR related to this process. These findings will enable more accurate and reliable normalization of qPCR results for gene expression studies in this economically important woody plant, particularly related to rooting and clonal propagation.

Reference gene selection for quantitative reverse transcription-polymerase chain reaction normalization during in vitro adventitious rooting in Eucalyptus globulus Labill

PubMed Central

2010-01-01

Background Eucalyptus globulus and its hybrids are very important for the cellulose and paper industry mainly due to their low lignin content and frost resistance. However, rooting of cuttings of this species is recalcitrant and exogenous auxin application is often necessary for good root development. To date one of the most accurate methods available for gene expression analysis is quantitative reverse transcription-polymerase chain reaction (qPCR); however, reliable use of this technique requires reference genes for normalization. There is no single reference gene that can be regarded as universal for all experiments and biological materials. Thus, the identification of reliable reference genes must be done for every species and experimental approach. The present study aimed at identifying suitable control genes for normalization of gene expression associated with adventitious rooting in E. globulus microcuttings. Results By the use of two distinct algorithms, geNorm and NormFinder, we have assessed gene expression stability of eleven candidate reference genes in E. globulus: 18S, ACT2, EF2, EUC12, H2B, IDH, SAND, TIP41, TUA, UBI and 33380. The candidate reference genes were evaluated in microccuttings rooted in vitro, in presence or absence of auxin, along six time-points spanning the process of adventitious rooting. Overall, the stability profiles of these genes determined with each one of the algorithms were very similar. Slight differences were observed in the most stable pair of genes indicated by each program: IDH and SAND for geNorm, and H2B and TUA for NormFinder. Both programs indentified UBI and 18S as the most variable genes. To validate these results and select the most suitable reference genes, the expression profile of the ARGONAUTE1 gene was evaluated in relation to the most stable candidate genes indicated by each algorithm. Conclusion Our study showed that expression stability varied between putative reference genes tested in E. globulus. Based on the AGO1 relative expression profile obtained using the genes suggested by the algorithms, H2B and TUA were considered as the most suitable reference genes for expression studies in E. globulus adventitious rooting. UBI and 18S were unsuitable for use as controls in qPCR related to this process. These findings will enable more accurate and reliable normalization of qPCR results for gene expression studies in this economically important woody plant, particularly related to rooting and clonal propagation. PMID:20854682

Multiplexed LC-MS/MS analysis of horse plasma proteins to study doping in sport.

PubMed

Barton, Chris; Beck, Paul; Kay, Richard; Teale, Phil; Roberts, Jane

2009-06-01

The development of protein biomarkers for the indirect detection of doping in horse is a potential solution to doping threats such as gene and protein doping. A method for biomarker candidate discovery in horse plasma is presented using targeted analysis of proteotypic peptides from horse proteins. These peptides were first identified in a novel list of the abundant proteins in horse plasma. To monitor these peptides, an LC-MS/MS method using multiple reaction monitoring was developed to study the quantity of 49 proteins in horse plasma in a single run. The method was optimised and validated, and then applied to a population of race-horses to study protein variance within a population. The method was finally applied to longitudinal time courses of horse plasma collected after administration of an anabolic steroid to demonstrate utility for hypothesis-driven discovery of doping biomarker candidates.

Novel strategies to mine alcoholism-related haplotypes and genes by combining existing knowledge framework.

PubMed

Zhang, RuiJie; Li, Xia; Jiang, YongShuai; Liu, GuiYou; Li, ChuanXing; Zhang, Fan; Xiao, Yun; Gong, BinSheng

2009-02-01

High-throughout single nucleotide polymorphism detection technology and the existing knowledge provide strong support for mining the disease-related haplotypes and genes. In this study, first, we apply four kinds of haplotype identification methods (Confidence Intervals, Four Gamete Tests, Solid Spine of LD and fusing method of haplotype block) into high-throughout SNP genotype data to identify blocks, then use cluster analysis to verify the effectiveness of the four methods, and select the alcoholism-related SNP haplotypes through risk analysis. Second, we establish a mapping from haplotypes to alcoholism-related genes. Third, we inquire NCBI SNP and gene databases to locate the blocks and identify the candidate genes. In the end, we make gene function annotation by KEGG, Biocarta, and GO database. We find 159 haplotype blocks, which relate to the alcoholism most possibly on chromosome 1 approximately 22, including 227 haplotypes, of which 102 SNP haplotypes may increase the risk of alcoholism. We get 121 alcoholism-related genes and verify their reliability by the functional annotation of biology. In a word, we not only can handle the SNP data easily, but also can locate the disease-related genes precisely by combining our novel strategies of mining alcoholism-related haplotypes and genes with existing knowledge framework.

The Candidate Cancer Gene Database: a database of cancer driver genes from forward genetic screens in mice.

PubMed

Abbott, Kenneth L; Nyre, Erik T; Abrahante, Juan; Ho, Yen-Yi; Isaksson Vogel, Rachel; Starr, Timothy K

2015-01-01

Identification of cancer driver gene mutations is crucial for advancing cancer therapeutics. Due to the overwhelming number of passenger mutations in the human tumor genome, it is difficult to pinpoint causative driver genes. Using transposon mutagenesis in mice many laboratories have conducted forward genetic screens and identified thousands of candidate driver genes that are highly relevant to human cancer. Unfortunately, this information is difficult to access and utilize because it is scattered across multiple publications using different mouse genome builds and strength metrics. To improve access to these findings and facilitate meta-analyses, we developed the Candidate Cancer Gene Database (CCGD, http://ccgd-starrlab.oit.umn.edu/). The CCGD is a manually curated database containing a unified description of all identified candidate driver genes and the genomic location of transposon common insertion sites (CISs) from all currently published transposon-based screens. To demonstrate relevance to human cancer, we performed a modified gene set enrichment analysis using KEGG pathways and show that human cancer pathways are highly enriched in the database. We also used hierarchical clustering to identify pathways enriched in blood cancers compared to solid cancers. The CCGD is a novel resource available to scientists interested in the identification of genetic drivers of cancer. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Integrated Systems Biology Analysis of Transcriptomes Reveals Candidate Genes for Acidity Control in Developing Fruits of Sweet Orange (Citrus sinensis L. Osbeck).

PubMed

Huang, Dingquan; Zhao, Yihong; Cao, Minghao; Qiao, Liang; Zheng, Zhi-Liang

2016-01-01

Organic acids, such as citrate and malate, are important contributors for the sensory traits of fleshy fruits. Although their biosynthesis has been illustrated, regulatory mechanisms of acid accumulation remain to be dissected. To provide transcriptional architecture and identify candidate genes for citrate accumulation in fruits, we have selected for transcriptome analysis four varieties of sweet orange (Citrus sinensis L. Osbeck) with varying fruit acidity, Succari (acidless), Bingtang (low acid), and Newhall and Xinhui (normal acid). Fruits of these varieties at 45 days post anthesis (DPA), which corresponds to Stage I (cell division), had similar acidity, but they displayed differential acid accumulation at 142 DPA (Stage II, cell expansion). Transcriptomes of fruits at 45 and 142 DPA were profiled using RNA sequencing and analyzed with three different algorithms (Pearson correlation, gene coexpression network and surrogate variable analysis). Our network analysis shows that the acid-correlated genes belong to three distinct network modules. Several of these candidate fruit acidity genes encode regulatory proteins involved in transport (such as AHA10), degradation (such as APD2) and transcription (such as AIL6) and act as hubs in the citrate accumulation gene networks. Taken together, our integrated systems biology analysis has provided new insights into the fruit citrate accumulation gene network and led to the identification of candidate genes likely associated with the fruit acidity control.

Integrated Systems Biology Analysis of Transcriptomes Reveals Candidate Genes for Acidity Control in Developing Fruits of Sweet Orange (Citrus sinensis L. Osbeck)

PubMed Central

Huang, Dingquan; Zhao, Yihong; Cao, Minghao; Qiao, Liang; Zheng, Zhi-Liang

2016-01-01

Organic acids, such as citrate and malate, are important contributors for the sensory traits of fleshy fruits. Although their biosynthesis has been illustrated, regulatory mechanisms of acid accumulation remain to be dissected. To provide transcriptional architecture and identify candidate genes for citrate accumulation in fruits, we have selected for transcriptome analysis four varieties of sweet orange (Citrus sinensis L. Osbeck) with varying fruit acidity, Succari (acidless), Bingtang (low acid), and Newhall and Xinhui (normal acid). Fruits of these varieties at 45 days post anthesis (DPA), which corresponds to Stage I (cell division), had similar acidity, but they displayed differential acid accumulation at 142 DPA (Stage II, cell expansion). Transcriptomes of fruits at 45 and 142 DPA were profiled using RNA sequencing and analyzed with three different algorithms (Pearson correlation, gene coexpression network and surrogate variable analysis). Our network analysis shows that the acid-correlated genes belong to three distinct network modules. Several of these candidate fruit acidity genes encode regulatory proteins involved in transport (such as AHA10), degradation (such as APD2) and transcription (such as AIL6) and act as hubs in the citrate accumulation gene networks. Taken together, our integrated systems biology analysis has provided new insights into the fruit citrate accumulation gene network and led to the identification of candidate genes likely associated with the fruit acidity control. PMID:27092171

Effector-mediated discovery of a novel resistance gene against Bremia lactucae in a nonhost lettuce species.

PubMed

Giesbers, Anne K J; Pelgrom, Alexandra J E; Visser, Richard G F; Niks, Rients E; Van den Ackerveken, Guido; Jeuken, Marieke J W

2017-11-01

Candidate effectors from lettuce downy mildew (Bremia lactucae) enable high-throughput germplasm screening for the presence of resistance (R) genes. The nonhost species Lactuca saligna comprises a source of B. lactucae R genes that has hardly been exploited in lettuce breeding. Its cross-compatibility with the host species L. sativa enables the study of inheritance of nonhost resistance (NHR). We performed transient expression of candidate RXLR effector genes from B. lactucae in a diverse Lactuca germplasm set. Responses to two candidate effectors (BLR31 and BLN08) were genetically mapped and tested for co-segregation with disease resistance. BLN08 induced a hypersensitive response (HR) in 55% of the L. saligna accessions, but responsiveness did not co-segregate with resistance to Bl:24. BLR31 triggered an HR in 5% of the L. saligna accessions, and revealed a novel R gene providing complete B. lactucae race Bl:24 resistance. Resistant hybrid plants that were BLR31 nonresponsive indicated other unlinked R genes and/or nonhost QTLs. We have identified a candidate avirulence effector of B. lactucae (BLR31) and its cognate R gene in L. saligna. Concurrently, our results suggest that R genes are not required for NHR of L. saligna. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

Genetic Architecture of Ear Fasciation in Maize (Zea mays) under QTL Scrutiny

PubMed Central

Mendes-Moreira, Pedro; Alves, Mara L.; Satovic, Zlatko; dos Santos, João Pacheco; Santos, João Nina; Souza, João Cândido; Pêgo, Silas E.; Hallauer, Arnel R.; Vaz Patto, Maria Carlota

2015-01-01

Maize ear fasciation Knowledge of the genes affecting maize ear inflorescence may lead to better grain yield modeling. Maize ear fasciation, defined as abnormal flattened ears with high kernel row number, is a quantitative trait widely present in Portuguese maize landraces. Material and Methods Using a segregating population derived from an ear fasciation contrasting cross (consisting of 149 F2:3 families) we established a two location field trial using a complete randomized block design. Correlations and heritabilities for several ear fasciation-related traits and yield were determined. Quantitative Trait Loci (QTL) involved in the inheritance of those traits were identified and candidate genes for these QTL proposed. Results and Discussion Ear fasciation broad-sense heritability was 0.73. Highly significant correlations were found between ear fasciation and some ear and cob diameters and row number traits. For the 23 yield and ear fasciation-related traits, 65 QTL were identified, out of which 11 were detected in both environments, while for the three principal components, five to six QTL were detected per environment. Detected QTL were distributed across 17 genomic regions and explained individually, 8.7% to 22.4% of the individual traits or principal components phenotypic variance. Several candidate genes for these QTL regions were proposed, such as bearded-ear1, branched silkless1, compact plant1, ramosa2, ramosa3, tasselseed4 and terminal ear1. However, many QTL mapped to regions without known candidate genes, indicating potential chromosomal regions not yet targeted for maize ear traits selection. Conclusions Portuguese maize germplasm represents a valuable source of genes or allelic variants for yield improvement and elucidation of the genetic basis of ear fasciation traits. Future studies should focus on fine mapping of the identified genomic regions with the aim of map-based cloning. PMID:25923975

Single Nucleotide Polymorphism in Gene Encoding Transcription Factor Prep1 Is Associated with HIV-1-Associated Dementia

PubMed Central

van Manen, Daniëlle; Bunnik, Evelien M.; van Sighem, Ard I.; Sieberer, Margit; Boeser-Nunnink, Brigitte; de Wolf, Frank; Schuitemaker, Hanneke; Portegies, Peter; Kootstra, Neeltje A.; van 't Wout, Angélique B.

2012-01-01

Background Infection with HIV-1 may result in severe cognitive and motor impairment, referred to as HIV-1-associated dementia (HAD). While its prevalence has dropped significantly in the era of combination antiretroviral therapy, milder neurocognitive disorders persist with a high prevalence. To identify additional therapeutic targets for treating HIV-associated neurocognitive disorders, several candidate gene polymorphisms have been evaluated, but few have been replicated across multiple studies. Methods We here tested 7 candidate gene polymorphisms for association with HAD in a case-control study consisting of 86 HAD cases and 246 non-HAD AIDS patients as controls. Since infected monocytes and macrophages are thought to play an important role in the infection of the brain, 5 recently identified single nucleotide polymorphisms (SNPs) affecting HIV-1 replication in macrophages in vitro were also tested. Results The CCR5 wt/Δ32 genotype was only associated with HAD in individuals who developed AIDS prior to 1991, in agreement with the observed fading effect of this genotype on viral load set point. A significant difference in genotype distribution among all cases and controls irrespective of year of AIDS diagnosis was found only for a SNP in candidate gene PREP1 (p = 1.2×10−5). Prep1 has recently been identified as a transcription factor preferentially binding the −2,518 G allele in the promoter of the gene encoding MCP-1, a protein with a well established role in the etiology of HAD. Conclusion These results support previous findings suggesting an important role for MCP-1 in the onset of HIV-1-associated neurocognitive disorders. PMID:22347417

A Genome Wide Association Study of arabinoxylan content in 2-row spring barley grain

PubMed Central

Hassan, Ali Saleh; Houston, Kelly; Lahnstein, Jelle; Shirley, Neil; Schwerdt, Julian G.; Gidley, Michael J.; Waugh, Robbie; Little, Alan

2017-01-01

In barley endosperm arabinoxylan (AX) is the second most abundant cell wall polysaccharide and in wheat it is the most abundant polysaccharide in the starchy endosperm walls of the grain. AX is one of the main contributors to grain dietary fibre content providing several health benefits including cholesterol and glucose lowering effects, and antioxidant activities. Due to its complex structural features, AX might also affect the downstream applications of barley grain in malting and brewing. Using a high pressure liquid chromatography (HPLC) method we quantified AX amounts in mature grain in 128 spring 2-row barley accessions. Amounts ranged from ~ 5.2 μg/g to ~ 9 μg/g. We used this data for a Genome Wide Association Study (GWAS) that revealed three significant quantitative trait loci (QTL) associated with grain AX levels which passed a false discovery threshold (FDR) and are located on two of the seven barley chromosomes. Regions underlying the QTLs were scanned for genes likely to be involved in AX biosynthesis or turnover, and strong candidates, including glycosyltransferases from the GT43 and GT61 families and glycoside hydrolases from the GH10 family, were identified. Phylogenetic trees of selected gene families were built based on protein translations and were used to examine the relationship of the barley candidate genes to those in other species. Our data reaffirms the roles of existing genes thought to contribute to AX content, and identifies novel QTL (and candidate genes associated with them) potentially influencing the AX content of barley grain. One potential outcome of this work is the deployment of highly associated single nucleotide polymorphisms markers in breeding programs to guide the modification of AX abundance in barley grain. PMID:28771585

Methylation signature of lymph node metastases in breast cancer patients

PubMed Central

2012-01-01

Background Invasion and metastasis are two important hallmarks of malignant tumors caused by complex genetic and epigenetic alterations. The present study investigated the contribution of aberrant methylation profiles of cancer related genes, APC, BIN1, BMP6, BRCA1, CST6, ESR-b, GSTP1, P14 (ARF), P16 (CDKN2A), P21 (CDKN1A), PTEN, and TIMP3, in the matched axillary lymph node metastasis in comparison to the primary tumor tissue and the adjacent normal tissue from the same breast cancer patients to identify the potential of candidate genes methylation as metastatic markers. Methods The quantitative methylation analysis was performed using the SEQUENOM’s EpiTYPER™ assay which relies on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Results The quantitative DNA methylation analysis of the candidate genes showed higher methylation proportion in the primary tumor tissue than that of the matched normal tissue and the differences were significant for the APC, BIN1, BMP6, BRCA1, CST6, ESR-b, P16, PTEN and TIMP3 promoter regions (P<0.05). Among those candidate methylated genes, APC, BMP6, BRCA1 and P16 displayed higher methylation proportion in the matched lymph node metastasis than that found in the normal tissue (P<0.05). The pathway analysis revealed that BMP6, BRCA1 and P16 have a role in prevention of neoplasm metastasis. Conclusions The results of the present study showed methylation heterogeneity between primary tumors and metastatic lesion. The contribution of aberrant methylation alterations of BMP6, BRCA1 and P16 genes in lymph node metastasis might provide a further clue to establish useful biomarkers for screening metastasis. PMID:22695536

Targeted resequencing of candidate genes reveals novel variants associated with severe Behçet's uveitis.

PubMed

Kim, Sang Jin; Lee, Seungbok; Park, Changho; Seo, Jeong-Sun; Kim, Jong-Il; Yu, Hyeong Gon

2013-10-18

Behçet's disease (BD) is a chronic systemic inflammatory disorder characterized by four major manifestations: recurrent uveitis, oral and genital ulcers and skin lesions. To identify some pathogenic variants associated with severe Behçet's uveitis, we used targeted and massively parallel sequencing methods to explore the genetic diversity of target regions. A solution-based target enrichment kit was designed to capture whole-exonic regions of 132 candidate genes. Using a multiplexing strategy, 32 samples from patients with a severe type of Behçet's uveitis were sequenced with a Genome Analyzer IIx. We compared the frequency of each variant with that of 59 normal Korean controls, and selected five rare and eight common single-nucleotide variants as the candidates for a replication study. The selected variants were genotyped in 61 cases and 320 controls and, as a result, two rare and seven common variants showed significant associations with severe Behçet's uveitis (P<0.05). Some of these, including rs199955684 in KIR3DL3, rs1801133 in MTHFR, rs1051790 in MICA and rs1051456 in KIR2DL4, were predicted to be damaging by either the PolyPhen-2 or SIFT prediction program. Variants on FCGR3A (rs396991) and ICAM1 (rs5498) have been previously reported as susceptibility loci of this disease, and those on IFNAR1, MTFHR and MICA also replicated the previous reports at the gene level. The KIR3DL3 and KIR2DL4 genes are novel susceptibility genes that have not been reported in association with BD. In conclusion, this study showed that target enrichment and next-generation sequencing technologies can provide valuable information on the genetic predisposition for Behçet's uveitis.

Ensemble positive unlabeled learning for disease gene identification.

PubMed

Yang, Peng; Li, Xiaoli; Chua, Hon-Nian; Kwoh, Chee-Keong; Ng, See-Kiong

2014-01-01

An increasing number of genes have been experimentally confirmed in recent years as causative genes to various human diseases. The newly available knowledge can be exploited by machine learning methods to discover additional unknown genes that are likely to be associated with diseases. In particular, positive unlabeled learning (PU learning) methods, which require only a positive training set P (confirmed disease genes) and an unlabeled set U (the unknown candidate genes) instead of a negative training set N, have been shown to be effective in uncovering new disease genes in the current scenario. Using only a single source of data for prediction can be susceptible to bias due to incompleteness and noise in the genomic data and a single machine learning predictor prone to bias caused by inherent limitations of individual methods. In this paper, we propose an effective PU learning framework that integrates multiple biological data sources and an ensemble of powerful machine learning classifiers for disease gene identification. Our proposed method integrates data from multiple biological sources for training PU learning classifiers. A novel ensemble-based PU learning method EPU is then used to integrate multiple PU learning classifiers to achieve accurate and robust disease gene predictions. Our evaluation experiments across six disease groups showed that EPU achieved significantly better results compared with various state-of-the-art prediction methods as well as ensemble learning classifiers. Through integrating multiple biological data sources for training and the outputs of an ensemble of PU learning classifiers for prediction, we are able to minimize the potential bias and errors in individual data sources and machine learning algorithms to achieve more accurate and robust disease gene predictions. In the future, our EPU method provides an effective framework to integrate the additional biological and computational resources for better disease gene predictions.

Functional dissection of drought-responsive gene expression patterns in Cynodon dactylon L.

PubMed

Kim, Changsoo; Lemke, Cornelia; Paterson, Andrew H

2009-05-01

Water deficit is one of the main abiotic factors that affect plant productivity in subtropical regions. To identify genes induced during the water stress response in Bermudagrass (Cynodon dactylon), cDNA macroarrays were used. The macroarray analysis identified 189 drought-responsive candidate genes from C. dactylon, of which 120 were up-regulated and 69 were down-regulated. The candidate genes were classified into seven groups by cluster analysis of expression levels across two intensities and three durations of imposed stress. Annotation using BLASTX suggested that up-regulated genes may be involved in proline biosynthesis, signal transduction pathways, protein repair systems, and removal of toxins, while down-regulated genes were mostly related to basic plant metabolism such as photosynthesis and glycolysis. The functional classification of gene ontology (GO) was consistent with the BLASTX results, also suggesting some crosstalk between abiotic and biotic stress. Comparative analysis of cis-regulatory elements from the candidate genes implicated specific elements in drought response in Bermudagrass. Although only a subset of genes was studied, Bermudagrass shared many drought-responsive genes and cis-regulatory elements with other botanical models, supporting a strategy of cross-taxon application of drought-responsive genes, regulatory cues, and physiological-genetic information.

BioGPS and MyGene.info: organizing online, gene-centric information.

PubMed

Wu, Chunlei; Macleod, Ian; Su, Andrew I

2013-01-01

Fast-evolving technologies have enabled researchers to easily generate data at genome scale, and using these technologies to compare biological states typically results in a list of candidate genes. Researchers are then faced with the daunting task of prioritizing these candidate genes for follow-up studies. There are hundreds, possibly even thousands, of web-based gene annotation resources available, but it quickly becomes impractical to manually access and review all of these sites for each gene in a candidate gene list. BioGPS (http://biogps.org) was created as a centralized gene portal for aggregating distributed gene annotation resources, emphasizing community extensibility and user customizability. BioGPS serves as a convenient tool for users to access known gene-centric resources, as well as a mechanism to discover new resources that were previously unknown to the user. This article describes updates to BioGPS made after its initial release in 2008. We summarize recent additions of features and data, as well as the robust user activity that underlies this community intelligence application. Finally, we describe MyGene.info (http://mygene.info) and related web services that provide programmatic access to BioGPS.

PGMapper: a web-based tool linking phenotype to genes.

PubMed

Xiong, Qing; Qiu, Yuhui; Gu, Weikuan

2008-04-01

With the availability of whole genome sequence in many species, linkage analysis, positional cloning and microarray are gradually becoming powerful tools for investigating the links between phenotype and genotype or genes. However, in these methods, causative genes underlying a quantitative trait locus, or a disease, are usually located within a large genomic region or a large set of genes. Examining the function of every gene is very time consuming and needs to retrieve and integrate the information from multiple databases or genome resources. PGMapper is a software tool for automatically matching phenotype to genes from a defined genome region or a group of given genes by combining the mapping information from the Ensembl database and gene function information from the OMIM and PubMed databases. PGMapper is currently available for candidate gene search of human, mouse, rat, zebrafish and 12 other species. Available online at http://www.genediscovery.org/pgmapper/index.jsp.

Candidate gene association mapping of Sclerotinia stalk rot resistance in sunflower (Helianthus annuus L.) uncovers the importance of COI1 homologs.

PubMed

Talukder, Zahirul I; Hulke, Brent S; Qi, Lili; Scheffler, Brian E; Pegadaraju, Venkatramana; McPhee, Kevin; Gulya, Thomas J

2014-01-01

Functional markers for Sclerotinia basal stalk rot resistance in sunflower were obtained using gene-level information from the model species Arabidopsis thaliana. Sclerotinia stalk rot, caused by Sclerotinia sclerotiorum, is one of the most destructive diseases of sunflower (Helianthus annuus L.) worldwide. Markers for genes controlling resistance to S. sclerotiorum will enable efficient marker-assisted selection (MAS). We sequenced eight candidate genes homologous to Arabidopsis thaliana defense genes known to be associated with Sclerotinia disease resistance in a sunflower association mapping population evaluated for Sclerotinia stalk rot resistance. The total candidate gene sequence regions covered a concatenated length of 3,791 bp per individual. A total of 187 polymorphic sites were detected for all candidate gene sequences, 149 of which were single nucleotide polymorphisms (SNPs) and 38 were insertions/deletions. Eight SNPs in the coding regions led to changes in amino acid codons. Linkage disequilibrium decay throughout the candidate gene regions declined on average to an r (2) = 0.2 for genetic intervals of 120 bp, but extended up to 350 bp with r (2) = 0.1. A general linear model with modification to account for population structure was found the best fitting model for this population and was used for association mapping. Both HaCOI1-1 and HaCOI1-2 were found to be strongly associated with Sclerotinia stalk rot resistance and explained 7.4 % of phenotypic variation in this population. These SNP markers associated with Sclerotinia stalk rot resistance can potentially be applied to the selection of favorable genotypes, which will significantly improve the efficiency of MAS during the development of stalk rot resistant cultivars.

Fine mapping of Restorer-of-fertility in pepper (Capsicum annuum L.) identified a candidate gene encoding a pentatricopeptide repeat (PPR)-containing protein.

PubMed

Jo, Yeong Deuk; Ha, Yeaseong; Lee, Joung-Ho; Park, Minkyu; Bergsma, Alex C; Choi, Hong-Il; Goritschnig, Sandra; Kloosterman, Bjorn; van Dijk, Peter J; Choi, Doil; Kang, Byoung-Cheorl

2016-10-01

Using fine mapping techniques, the genomic region co-segregating with Restorer - of - fertility ( Rf ) in pepper was delimited to a region of 821 kb in length. A PPR gene in this region, CaPPR6 , was identified as a strong candidate for Rf based on expression pattern and characteristics of encoding sequence. Cytoplasmic-genic male sterility (CGMS) has been used for the efficient production of hybrid seeds in peppers (Capsicum annuum L.). Although the mitochondrial candidate genes that might be responsible for cytoplasmic male sterility (CMS) have been identified, the nuclear Restorer-of-fertility (Rf) gene has not been isolated. To identify the genomic region co-segregating with Rf in pepper, we performed fine mapping using an Rf-segregating population consisting of 1068 F2 individuals, based on BSA-AFLP and a comparative mapping approach. Through six cycles of chromosome walking, the co-segregating region harboring the Rf locus was delimited to be within 821 kb of sequence. Prediction of expressed genes in this region based on transcription analysis revealed four candidate genes. Among these, CaPPR6 encodes a pentatricopeptide repeat (PPR) protein with PPR motifs that are repeated 14 times. Characterization of the CaPPR6 protein sequence, based on alignment with other homologs, showed that CaPPR6 is a typical Rf-like (RFL) gene reported to have undergone diversifying selection during evolution. A marker developed from a sequence near CaPPR6 showed a higher prediction rate of the Rf phenotype than those of previously developed markers when applied to a panel of breeding lines of diverse origin. These results suggest that CaPPR6 is a strong candidate for the Rf gene in pepper.

Analysis of shared homozygosity regions in Saudi siblings with attention deficit hyperactivity disorder.

PubMed

Shinwari, Jameela M A; Al Yemni, Eman A A; Alnaemi, Faten M; Abebe, Dejene; Al-Abdulaziz, Basma S; Al Mubarak, Bashayer R; Ghaziuddin, Mohammad; Al Tassan, Nada A

2017-08-01

Genetic and clinical complexities are common features of most psychiatric illnesses that pose a major obstacle in risk-gene identification. Attention deficit hyperactivity disorder (ADHD) is the most prevalent child-onset psychiatric illness, with high heritability. Over the past decade, numerous genetic studies utilizing various approaches, such as genome-wide association, candidate-gene association, and linkage analysis, have identified a multitude of candidate loci/genes. However, such studies have yielded diverse findings that are rarely reproduced, indicating that other genetic determinants have not been discovered yet. In this study, we carried out sib-pair analysis on seven multiplex families with ADHD from Saudi Arabia. We aimed to identify the candidate chromosomal regions and genes linked to the disease. A total of 41 individuals from multiplex families were analyzed for shared regions of homozygosity. Genes within these regions were prioritized according to their potential relevance to ADHD. We identified multiple genomic regions spanning different chromosomes to be shared among affected members of each family; these included chromosomes 3, 5, 6, 7, 8, 9, 10, 13, 17, and 18. We also found specific regions on chromosomes 8 and 17 to be shared between affected individuals from more than one family. Among the genes present in the regions reported here were involved in neurotransmission (GRM3, SIGMAR1, CHAT, and SLC18A3) and members of the HLA gene family (HLA-A, HLA-DPA1, and MICC). The candidate regions identified in this study highlight the genetic diversity of ADHD. Upon further investigation, these loci may reveal candidate genes that enclose variants associated with ADHD. Although most ADHD studies were conducted in other populations, our study provides insight from an understudied, ethnically interesting population.

Candidate genes and adaptive radiation: insights from transcriptional adaptation to the limnetic niche among coregonine fishes (Coregonus spp., Salmonidae).

PubMed

Jeukens, Julie; Bittner, David; Knudsen, Rune; Bernatchez, Louis

2009-01-01

In the past 40 years, there has been increasing acceptance that variation in levels of gene expression represents a major source of evolutionary novelty. Gene expression divergence is therefore likely to be involved in the emergence of incipient species, namely, in a context of adaptive radiation. In the lake whitefish species complex (Coregonus clupeaformis), previous microarray experiments have led to the identification of candidate genes potentially implicated in the parallel evolution of the limnetic dwarf lake whitefish, which is highly distinct from the benthic normal lake whitefish in life history, morphology, metabolism, and behavior, and yet diverged from it only approximately 15,000 years before present. The aim of the present study was to address transcriptional divergence for six candidate genes among lake whitefish and European whitefish (Coregonus lavaretus) species pairs, as well as lake cisco (Coregonus artedi) and vendace (Coregonus albula). The main goal was to test the hypothesis that parallel phenotypic adaptation toward the use of the limnetic niche in coregonine fishes is accompanied by parallelism in candidate gene transcription as measured by quantitative real-time polymerase chain reaction. Results obtained for three candidate genes, whereby parallelism in expression was observed across all whitefish species pairs, provide strong support for the hypothesis that divergent natural selection plays an important role in the adaptive radiation of whitefish species. However, this parallelism in expression did not extend to cisco and vendace, thereby infirming transcriptional convergence between limnetic whitefish species and their limnetic congeners for these genes. As recently proposed (Lynch 2007a. The evolution of genetic networks by non-adaptive processes. Nat Rev Genet. 8:803-813), these results may suggest that convergent phenotypic evolution can result from nonadaptive shaping of genome architecture in independently evolved coregonine lineages.

Genetic subdivision and candidate genes under selection in North American grey wolves.

PubMed

Schweizer, Rena M; vonHoldt, Bridgett M; Harrigan, Ryan; Knowles, James C; Musiani, Marco; Coltman, David; Novembre, John; Wayne, Robert K

2016-01-01

Previous genetic studies of the highly mobile grey wolf (Canis lupus) found population structure that coincides with habitat and phenotype differences. We hypothesized that these ecologically distinct populations (ecotypes) should exhibit signatures of selection in genes related to morphology, coat colour and metabolism. To test these predictions, we quantified population structure related to habitat using a genotyping array to assess variation in 42 036 single-nucleotide polymorphisms (SNPs) in 111 North American grey wolves. Using these SNP data and individual-level measurements of 12 environmental variables, we identified six ecotypes: West Forest, Boreal Forest, Arctic, High Arctic, British Columbia and Atlantic Forest. Next, we explored signals of selection across these wolf ecotypes through the use of three complementary methods to detect selection: FST /haplotype homozygosity bivariate percentilae, bayescan, and environmentally correlated directional selection with bayenv. Across all methods, we found consistent signals of selection on genes related to morphology, coat coloration, metabolism, as predicted, as well as vision and hearing. In several high-ranking candidate genes, including LEPR, TYR and SLC14A2, we found variation in allele frequencies that follow environmental changes in temperature and precipitation, a result that is consistent with local adaptation rather than genetic drift. Our findings show that local adaptation can occur despite gene flow in a highly mobile species and can be detected through a moderately dense genomic scan. These patterns of local adaptation revealed by SNP genotyping likely reflect high fidelity to natal habitats of dispersing wolves, strong ecological divergence among habitats, and moderate levels of linkage in the wolf genome. © 2015 John Wiley & Sons Ltd.

Global Transcriptome Changes Underlying Colony Growth in the Opportunistic Human Pathogen Aspergillus fumigatus

PubMed Central

Gibbons, John G.; Beauvais, Anne; Beau, Remi; McGary, Kriston L.

2012-01-01

Aspergillus fumigatus is the most common and deadly pulmonary fungal infection worldwide. In the lung, the fungus usually forms a dense colony of filaments embedded in a polymeric extracellular matrix. To identify candidate genes involved in this biofilm (BF) growth, we used RNA-Seq to compare the transcriptomes of BF and liquid plankton (PL) growth. Sequencing and mapping of tens of millions sequence reads against the A. fumigatus transcriptome identified 3,728 differentially regulated genes in the two conditions. Although many of these genes, including the ones coding for transcription factors, stress response, the ribosome, and the translation machinery, likely reflect the different growth demands in the two conditions, our experiment also identified hundreds of candidate genes for the observed differences in morphology and pathobiology between BF and PL. We found an overrepresentation of upregulated genes in transport, secondary metabolism, and cell wall and surface functions. Furthermore, upregulated genes showed significant spatial structure across the A. fumigatus genome; they were more likely to occur in subtelomeric regions and colocalized in 27 genomic neighborhoods, many of which overlapped with known or candidate secondary metabolism gene clusters. We also identified 1,164 genes that were downregulated. This gene set was not spatially structured across the genome and was overrepresented in genes participating in primary metabolic functions, including carbon and amino acid metabolism. These results add valuable insight into the genetics of biofilm formation in A. fumigatus and other filamentous fungi and identify many relevant, in the context of biofilm biology, candidate genes for downstream functional experiments. PMID:21724936

Progress Report for DOE DE-FG03-98ER20317 ''Regulation of the floral homeotic gene AGAMOUS'' Current and Final Funding Period: September 1, 2002, to December 31, 2002

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weigel, D.

2003-03-11

OAK-B135 Results obtained during this funding period: (1) Phylogenetic footprinting of AG regulatory sequences Sequences necessary and sufficient for AGAMOUS (AG) expression in the center of Arabidopsis flowers are located in the second intron, which is about 3 kb in size. This intron contains binding sites for two transcription factors, LEAFY (LFY) and WUSCHEL (WUS), which are direct activators of AG. We used the new method of phylogenetic shadowing to identify new regulatory elements. Among 29 Brassicaceae, several other motifs, but not the LFY and WUS binding sites previously identified, are largely invariant. Using reporter gene analyses, we tested sixmore » of these motifs and found that they are all functionally important for activity of AG regulatory sequences in A. thaliana. (2) Repression of AG by MADS box genes A candidate for repressing AG in the shoot apical meristem has been the MADS box gene FUL, since it is expressed in the shoot apical meristem and since an activated version (FUL:VP16) leads to ectopic AG expression in the shoot apical meristem. However, there is no ectopic AG expression in full single mutants. We therefore started to generate VP16 fusions of several other MADS box genes expressed in the shoot apical meristem, to determine which of these might be candidates for FUL redundant genes. We found that AGL6:VP16 has a similar phenotype as FUL:VP16, suggesting that AGL6 and FUL interact. We are now testing this hypothesis. (3) Two candidate AG regulators, WOW and ULA Because the phylogenetic footprinting project has identified several new candidate regulatory motifs, of which at least one (the CCAATCA motif) has rather strong effects, we had decided to put the analysis of WOW and ULA on hold, and to focus on using the newly identified motifs as tools. We conduct ed yeast one-hybrid screen with two of the conserved motifs, and identified several classes of transcription factors that can interact with them. One of these is encoded by the PAN gene, previously known to be expressed in a domain that overlaps the AG domain, but not known before to regulate AG. (4) New genetic modifiers of AG This part of the project was concluded in the previous funding period.« less

Reconstruction of a Functional Human Gene Network, with an Application for Prioritizing Positional Candidate Genes

PubMed Central

Franke, Lude; Bakel, Harm van; Fokkens, Like; de Jong, Edwin D.; Egmont-Petersen, Michael; Wijmenga, Cisca

2006-01-01

Most common genetic disorders have a complex inheritance and may result from variants in many genes, each contributing only weak effects to the disease. Pinpointing these disease genes within the myriad of susceptibility loci identified in linkage studies is difficult because these loci may contain hundreds of genes. However, in any disorder, most of the disease genes will be involved in only a few different molecular pathways. If we know something about the relationships between the genes, we can assess whether some genes (which may reside in different loci) functionally interact with each other, indicating a joint basis for the disease etiology. There are various repositories of information on pathway relationships. To consolidate this information, we developed a functional human gene network that integrates information on genes and the functional relationships between genes, based on data from the Kyoto Encyclopedia of Genes and Genomes, the Biomolecular Interaction Network Database, Reactome, the Human Protein Reference Database, the Gene Ontology database, predicted protein-protein interactions, human yeast two-hybrid interactions, and microarray coexpressions. We applied this network to interrelate positional candidate genes from different disease loci and then tested 96 heritable disorders for which the Online Mendelian Inheritance in Man database reported at least three disease genes. Artificial susceptibility loci, each containing 100 genes, were constructed around each disease gene, and we used the network to rank these genes on the basis of their functional interactions. By following up the top five genes per artificial locus, we were able to detect at least one known disease gene in 54% of the loci studied, representing a 2.8-fold increase over random selection. This suggests that our method can significantly reduce the cost and effort of pinpointing true disease genes in analyses of disorders for which numerous loci have been reported but for which most of the genes are unknown. PMID:16685651

Identification of reference genes for quantitative expression analysis using large-scale RNA-seq data of Arabidopsis thaliana and model crop plants.

PubMed

Kudo, Toru; Sasaki, Yohei; Terashima, Shin; Matsuda-Imai, Noriko; Takano, Tomoyuki; Saito, Misa; Kanno, Maasa; Ozaki, Soichi; Suwabe, Keita; Suzuki, Go; Watanabe, Masao; Matsuoka, Makoto; Takayama, Seiji; Yano, Kentaro

2016-10-13

In quantitative gene expression analysis, normalization using a reference gene as an internal control is frequently performed for appropriate interpretation of the results. Efforts have been devoted to exploring superior novel reference genes using microarray transcriptomic data and to evaluating commonly used reference genes by targeting analysis. However, because the number of specifically detectable genes is totally dependent on probe design in the microarray analysis, exploration using microarray data may miss some of the best choices for the reference genes. Recently emerging RNA sequencing (RNA-seq) provides an ideal resource for comprehensive exploration of reference genes since this method is capable of detecting all expressed genes, in principle including even unknown genes. We report the results of a comprehensive exploration of reference genes using public RNA-seq data from plants such as Arabidopsis thaliana (Arabidopsis), Glycine max (soybean), Solanum lycopersicum (tomato) and Oryza sativa (rice). To select reference genes suitable for the broadest experimental conditions possible, candidates were surveyed by the following four steps: (1) evaluation of the basal expression level of each gene in each experiment; (2) evaluation of the expression stability of each gene in each experiment; (3) evaluation of the expression stability of each gene across the experiments; and (4) selection of top-ranked genes, after ranking according to the number of experiments in which the gene was expressed stably. Employing this procedure, 13, 10, 12 and 21 top candidates for reference genes were proposed in Arabidopsis, soybean, tomato and rice, respectively. Microarray expression data confirmed that the expression of the proposed reference genes under broad experimental conditions was more stable than that of commonly used reference genes. These novel reference genes will be useful for analyzing gene expression profiles across experiments carried out under various experimental conditions.

Genealogy-based methods for inference of historical recombination and gene flow and their application in Saccharomyces cerevisiae.

PubMed

Jenkins, Paul A; Song, Yun S; Brem, Rachel B

2012-01-01

Genetic exchange between isolated populations, or introgression between species, serves as a key source of novel genetic material on which natural selection can act. While detecting historical gene flow from DNA sequence data is of much interest, many existing methods can be limited by requirements for deep population genomic sampling. In this paper, we develop a scalable genealogy-based method to detect candidate signatures of gene flow into a given population when the source of the alleles is unknown. Our method does not require sequenced samples from the source population, provided that the alleles have not reached fixation in the sampled recipient population. The method utilizes recent advances in algorithms for the efficient reconstruction of ancestral recombination graphs, which encode genealogical histories of DNA sequence data at each site, and is capable of detecting the signatures of gene flow whose footprints are of length up to single genes. Further, we employ a theoretical framework based on coalescent theory to test for statistical significance of certain recombination patterns consistent with gene flow from divergent sources. Implementing these methods for application to whole-genome sequences of environmental yeast isolates, we illustrate the power of our approach to highlight loci with unusual recombination histories. By developing innovative theory and methods to analyze signatures of gene flow from population sequence data, our work establishes a foundation for the continued study of introgression and its evolutionary relevance.

Genealogy-Based Methods for Inference of Historical Recombination and Gene Flow and Their Application in Saccharomyces cerevisiae

PubMed Central

Jenkins, Paul A.; Song, Yun S.; Brem, Rachel B.

2012-01-01

Genetic exchange between isolated populations, or introgression between species, serves as a key source of novel genetic material on which natural selection can act. While detecting historical gene flow from DNA sequence data is of much interest, many existing methods can be limited by requirements for deep population genomic sampling. In this paper, we develop a scalable genealogy-based method to detect candidate signatures of gene flow into a given population when the source of the alleles is unknown. Our method does not require sequenced samples from the source population, provided that the alleles have not reached fixation in the sampled recipient population. The method utilizes recent advances in algorithms for the efficient reconstruction of ancestral recombination graphs, which encode genealogical histories of DNA sequence data at each site, and is capable of detecting the signatures of gene flow whose footprints are of length up to single genes. Further, we employ a theoretical framework based on coalescent theory to test for statistical significance of certain recombination patterns consistent with gene flow from divergent sources. Implementing these methods for application to whole-genome sequences of environmental yeast isolates, we illustrate the power of our approach to highlight loci with unusual recombination histories. By developing innovative theory and methods to analyze signatures of gene flow from population sequence data, our work establishes a foundation for the continued study of introgression and its evolutionary relevance. PMID:23226196

Gene expression profiling reveals candidate genes related to residual feed intake in duodenum of laying ducks.

PubMed

Zeng, T; Huang, L; Ren, J; Chen, L; Tian, Y; Huang, Y; Zhang, H; Du, J; Lu, L

2017-12-01

Feed represents two-thirds of the total costs of poultry production, especially in developing countries. Improvement in feed efficiency would reduce the amount of feed required for production (growth or laying), the production cost, and the amount of nitrogenous waste. The most commonly used measures for feed efficiency are feed conversion ratio (FCR) and residual feed intake (RFI). As a more suitable indicator assessing feed efficiency, RFI is defined as the difference between observed and expected feed intake based on maintenance and growth or laying. However, the genetic and biological mechanisms regulating RFI are largely unknown. Identifying molecular mechanisms explaining divergence in RFI in laying ducks would lead to the development of early detection methods for the selection of more efficient breeding poultry. The objective of this study was to identify duodenum genes and pathways through transcriptional profiling in 2 extreme RFI phenotypes (HRFI and LRFI) of the duck population. Phenotypic aspects of feed efficiency showed that RFI was strongly positive with FCR and feed intake (FI). Transcriptomic analysis identified 35 differentially expressed genes between LRFI and HRFI ducks. These genes play an important role in metabolism, digestibility, secretion, and innate immunity including (), (), (), β (), and (). These results improve our knowledge of the biological basis underlying RFI, which would be useful for further investigations of key candidate genes for RFI and for the development of biomarkers.

Type of Renal Replacement Therapy (Hemodialysis versus Peritoneal Dialysis) Does Not Affect Cytokine Gene Expression or Clinical Parameters of Renal Transplant Candidates

PubMed Central

Kamińska, Dorota; Kościelska-Kasprzak, Katarzyna; Chudoba, Paweł; Mazanowska, Oktawia; Banasik, Mirosław; Żabinska, Marcelina; Boratyńska, Maria; Lepiesza, Agnieszka; Korta, Krzysztof; Gomółkiewicz, Agnieszka; Dzięgiel, Piotr; Klinger, Marian

2015-01-01

Patients with renal failure suffer from immune disturbances, caused by uremic toxins and influenced by dialysis treatment. The aim of the present study was to reveal whether type of dialysis modality (hemodialysis, HD, versus peritoneal dialysis, PD) differentially affects the immunocompetence, particularly the expression of genes involved in the immune response. Material. 87 renal transplant candidates (66 HD, 21 PD) were included in the study. Methods. The peripheral blood RNA samples were obtained with the PAXgene Blood system just before transplantation. The gene expression of CASP3, FAS, TP53, FOXP3, IFNG, IL2, IL6, IL8, IL10, IL17, IL18, LCN2, TGFB1, and TNF was assessed with real-time PCR on custom-designed low density arrays (TaqMan). Gene expression data were analyzed in relation to pretransplant clinical parameters. Results. The mean expression of examined genes showed no significant differences between PD and HD with the exception of FAS, expression of which was 30% higher in PD patients compared to the HD group. There was nonsignificantly higher expression of proinflammatory cytokines in the PD group. The clinical inflammatory parameters (CRP, albumin, cholesterol, and hemoglobin levels) did not differ between the groups. Conclusion. Type of renal replacement therapy exerts no differential effect on cytokine gene expression or inflammatory clinical parameters. PMID:26236736

Functional molecular markers for crop improvement.

PubMed

Kage, Udaykumar; Kumar, Arun; Dhokane, Dhananjay; Karre, Shailesh; Kushalappa, Ajjamada C

2016-10-01

A tremendous decline in cultivable land and resources and a huge increase in food demand calls for immediate attention to crop improvement. Though molecular plant breeding serves as a viable solution and is considered as "foundation for twenty-first century crop improvement", a major stumbling block for crop improvement is the availability of a limited functional gene pool for cereal crops. Advancement in the next generation sequencing (NGS) technologies integrated with tools like metabolomics, proteomics and association mapping studies have facilitated the identification of candidate genes, their allelic variants and opened new avenues to accelerate crop improvement through development and use of functional molecular markers (FMMs). The FMMs are developed from the sequence polymorphisms present within functional gene(s) which are associated with phenotypic trait variations. Since FMMs obviate the problems associated with random DNA markers, these are considered as "the holy grail" of plant breeders who employ targeted marker assisted selections (MAS) for crop improvement. This review article attempts to consider the current resources and novel methods such as metabolomics, proteomics and association studies for the identification of candidate genes and their validation through virus-induced gene silencing (VIGS) for the development of FMMs. A number of examples where the FMMs have been developed and used for the improvement of cereal crops for agronomic, food quality, disease resistance and abiotic stress tolerance traits have been considered.

Candidate Luminal B Breast Cancer Genes Identified by Genome, Gene Expression and DNA Methylation Profiling

PubMed Central

Addou-Klouche, Lynda; Finetti, Pascal; Saade, Marie-Rose; Manai, Marwa; Carbuccia, Nadine; Bekhouche, Ismahane; Letessier, Anne; Charafe-Jauffret, Emmanuelle; Jacquemier, Jocelyne; Spicuglia, Salvatore; de The, Hugues; Viens, Patrice; Bertucci, François; Birnbaum, Daniel; Chaffanet, Max

2014-01-01

Breast cancers (BCs) of the luminal B subtype are estrogen receptor-positive (ER+), highly proliferative, resistant to standard therapies and have a poor prognosis. To better understand this subtype we compared DNA copy number aberrations (CNAs), DNA promoter methylation, gene expression profiles, and somatic mutations in nine selected genes, in 32 luminal B tumors with those observed in 156 BCs of the other molecular subtypes. Frequent CNAs included 8p11-p12 and 11q13.1-q13.2 amplifications, 7q11.22-q34, 8q21.12-q24.23, 12p12.3-p13.1, 12q13.11-q24.11, 14q21.1-q23.1, 17q11.1-q25.1, 20q11.23-q13.33 gains and 6q14.1-q24.2, 9p21.3-p24,3, 9q21.2, 18p11.31-p11.32 losses. A total of 237 and 101 luminal B-specific candidate oncogenes and tumor suppressor genes (TSGs) presented a deregulated expression in relation with their CNAs, including 11 genes previously reported associated with endocrine resistance. Interestingly, 88% of the potential TSGs are located within chromosome arm 6q, and seven candidate oncogenes are potential therapeutic targets. A total of 100 candidate oncogenes were validated in a public series of 5,765 BCs and the overexpression of 67 of these was associated with poor survival in luminal tumors. Twenty-four genes presented a deregulated expression in relation with a high DNA methylation level. FOXO3, PIK3CA and TP53 were the most frequent mutated genes among the nine tested. In a meta-analysis of next-generation sequencing data in 875 BCs, KCNB2 mutations were associated with luminal B cases while candidate TSGs MDN1 (6q15) and UTRN (6q24), were mutated in this subtype. In conclusion, we have reported luminal B candidate genes that may play a role in the development and/or hormone resistance of this aggressive subtype. PMID:24416132

Genetics of human neural tube defects

PubMed Central

Greene, Nicholas D.E.; Stanier, Philip; Copp, Andrew J.

2009-01-01

Neural tube defects (NTDs) are common, severe congenital malformations whose causation involves multiple genes and environmental factors. Although more than 200 genes are known to cause NTDs in mice, there has been rather limited progress in delineating the molecular basis underlying most human NTDs. Numerous genetic studies have been carried out to investigate candidate genes in cohorts of patients, with particular reference to those that participate in folate one-carbon metabolism. Although the homocysteine remethylation gene MTHFR has emerged as a risk factor in some human populations, few other consistent findings have resulted from this approach. Similarly, attention focused on the human homologues of mouse NTD genes has contributed only limited positive findings to date, although an emerging association between genes of the non-canonical Wnt (planar cell polarity) pathway and NTDs provides candidates for future studies. Priorities for the next phase of this research include: (i) larger studies that are sufficiently powered to detect significant associations with relatively minor risk factors; (ii) analysis of multiple candidate genes in groups of well-genotyped individuals to detect possible gene–gene interactions; (iii) use of high throughput genomic technology to evaluate the role of copy number variants and to detect ‘private’ and regulatory mutations, neither of which have been studied to date; (iv) detailed analysis of patient samples stratified by phenotype to enable, for example, hypothesis-driven testing of candidates genes in groups of NTDs with specific defects of folate metabolism, or in groups of fetuses with well-defined phenotypes such as craniorachischisis. PMID:19808787

Genetic analysis of the calcineurin pathway identifies members of the EGR gene family, specifically EGR3, as potential susceptibility candidates in schizophrenia

PubMed Central

Yamada, Kazuo; Gerber, David J.; Iwayama, Yoshimi; Ohnishi, Tetsuo; Ohba, Hisako; Toyota, Tomoko; Aruga, Jun; Minabe, Yoshio; Tonegawa, Susumu; Yoshikawa, Takeo

2007-01-01

The calcineurin cascade is central to neuronal signal transduction, and genes in this network are intriguing candidate schizophrenia susceptibility genes. To replicate and extend our previously reported association between the PPP3CC gene, encoding the calcineurin catalytic γ-subunit, and schizophrenia, we examined 84 SNPs from 14 calcineurin-related candidate genes for genetic association by using 124 Japanese schizophrenic pedigrees. Four of these genes (PPP3CC, EGR2, EGR3, and EGR4) showed nominally significant association with schizophrenia. In a postmortem brain study, EGR1, EGR2, and EGR3 transcripts were shown to be down-regulated in the prefrontal cortex of schizophrenic, but not bipolar, patients. These findings raise a potentially important role for EGR genes in schizophrenia pathogenesis. Because EGR3 is an attractive candidate gene based on its chromosomal location close to PPP3CC within 8p21.3 and its functional link to dopamine, glutamate, and neuregulin signaling, we extended our analysis by resequencing the entire EGR3 genomic interval and detected 15 SNPs. One of these, IVS1 + 607A→G SNP, displayed the strongest evidence for disease association, which was confirmed in 1,140 independent case-control samples. An in vitro promoter assay detected a possible expression-regulatory effect of this SNP. These findings support the previous genetic association of altered calcineurin signaling with schizophrenia pathogenesis and identify EGR3 as a compelling susceptibility gene. PMID:17360599

Clinical application of antidepressant pharmacogenetics: considerations for the design of future studies.

PubMed

Fabbri, Chiara; Serretti, Alessandro

2018-06-12

A frustrating inertia has affected the development of clinical applications of antidepressant pharmacogenetics and personalized treatments of depression are still lacking 20 years after the first findings. Candidate gene studies provided replicated findings for some polymorphisms, but each of them shows at best a small effect on antidepressant efficacy and the cumulative effect of different polymorphisms is unclear. Further, no candidate was immune by at least some negative studies. These considerations give rise to some concerns about the clinical benefits of currently available pharmacogenetic tests since they are based on the results of candidate gene studies. Clinical guidelines in fact suggest that only polymorphisms that alter cytochrome 2D6 or 2C19 enzymatic activity probably provide useful clinical indications, while variants in genes involved in antidepressant pharmacodynamics have no recommended clinical applications. The present review discusses possible strategies to facilitate the identification of genetic biomarkers with clinical usefulness in guiding antidepressant treatments. These include analysis methods for the study of the polygenic/omnigenic nature of antidepressant response, the prioritization of polymorphisms on the basis of functional considerations, the incorporation of clinical-demographic predictors in pharmacogenetic studies (e.g. mixed polygenic and clinical risk scores), the application of methodological improvements to the design of future studies in order to maximize the comparability of results and improve power. Copyright © 2018. Published by Elsevier B.V.

Candidate innate immune system gene expression in the ecological model Daphnia

PubMed Central

Decaestecker, Ellen; Labbé, Pierrick; Ellegaard, Kirsten; Allen, Judith E.; Little, Tom J.

2011-01-01

The last ten years have witnessed increasing interest in host–pathogen interactions involving invertebrate hosts. The invertebrate innate immune system is now relatively well characterised, but in a limited range of genetic model organisms and under a limited number of conditions. Immune systems have been little studied under real-world scenarios of environmental variation and parasitism. Thus, we have investigated expression of candidate innate immune system genes in the water flea Daphnia, a model organism for ecological genetics, and whose capacity for clonal reproduction facilitates an exceptionally rigorous control of exposure dose or the study of responses at many time points. A unique characteristic of the particular Daphnia clones and pathogen strain combinations used presently is that they have been shown to be involved in specific host–pathogen coevolutionary interactions in the wild. We choose five genes, which are strong candidates to be involved in Daphnia–pathogen interactions, given that they have been shown to code for immune effectors in related organisms. Differential expression of these genes was quantified by qRT-PCR following exposure to the bacterial pathogen Pasteuria ramosa. Constitutive expression levels differed between host genotypes, and some genes appeared to show correlated expression. However, none of the genes appeared to show a major modification of expression level in response to Pasteuria exposure. By applying knowledge from related genetic model organisms (e.g. Drosophila) to models for the study of evolutionary ecology and coevolution (i.e. Daphnia), the candidate gene approach is temptingly efficient. However, our results show that detection of only weak patterns is likely if one chooses target genes for study based on previously identified genome sequences by comparison to homologues from other related organisms. Future work on the Daphnia–Pasteuria system will need to balance a candidate gene approach with more comprehensive approaches to de novo identify immune system genes specific to the Daphnia–Pasteuria interaction. PMID:21550363

Candidate innate immune system gene expression in the ecological model Daphnia.

PubMed

Decaestecker, Ellen; Labbé, Pierrick; Ellegaard, Kirsten; Allen, Judith E; Little, Tom J

2011-10-01

The last ten years have witnessed increasing interest in host-pathogen interactions involving invertebrate hosts. The invertebrate innate immune system is now relatively well characterised, but in a limited range of genetic model organisms and under a limited number of conditions. Immune systems have been little studied under real-world scenarios of environmental variation and parasitism. Thus, we have investigated expression of candidate innate immune system genes in the water flea Daphnia, a model organism for ecological genetics, and whose capacity for clonal reproduction facilitates an exceptionally rigorous control of exposure dose or the study of responses at many time points. A unique characteristic of the particular Daphnia clones and pathogen strain combinations used presently is that they have been shown to be involved in specific host-pathogen coevolutionary interactions in the wild. We choose five genes, which are strong candidates to be involved in Daphnia-pathogen interactions, given that they have been shown to code for immune effectors in related organisms. Differential expression of these genes was quantified by qRT-PCR following exposure to the bacterial pathogen Pasteuria ramosa. Constitutive expression levels differed between host genotypes, and some genes appeared to show correlated expression. However, none of the genes appeared to show a major modification of expression level in response to Pasteuria exposure. By applying knowledge from related genetic model organisms (e.g. Drosophila) to models for the study of evolutionary ecology and coevolution (i.e. Daphnia), the candidate gene approach is temptingly efficient. However, our results show that detection of only weak patterns is likely if one chooses target genes for study based on previously identified genome sequences by comparison to homologues from other related organisms. Future work on the Daphnia-Pasteuria system will need to balance a candidate gene approach with more comprehensive approaches to de novo identify immune system genes specific to the Daphnia-Pasteuria interaction. Copyright © 2011 Elsevier Ltd. All rights reserved.

Identification of KIF3A as a Novel Candidate Gene for Childhood Asthma Using RNA Expression and Population Allelic Frequencies Differences

PubMed Central

Butsch Kovacic, Melinda; Biagini Myers, Jocelyn M.; Wang, Ning; Martin, Lisa J.; Lindsey, Mark; Ericksen, Mark B.; He, Hua; Patterson, Tia L.; Baye, Tesfaye M.; Torgerson, Dara; Roth, Lindsey A.; Gupta, Jayanta; Sivaprasad, Umasundari; Gibson, Aaron M.; Tsoras, Anna M.; Hu, Donglei; Eng, Celeste; Chapela, Rocío; Rodríguez-Santana, José R.; Rodríguez-Cintrón, William; Avila, Pedro C.; Beckman, Kenneth; Seibold, Max A.; Gignoux, Chris; Musaad, Salma M.; Chen, Weiguo; Burchard, Esteban González; Khurana Hershey, Gurjit K.

2011-01-01

Background Asthma is a chronic inflammatory disease with a strong genetic predisposition. A major challenge for candidate gene association studies in asthma is the selection of biologically relevant genes. Methodology/Principal Findings Using epithelial RNA expression arrays, HapMap allele frequency variation, and the literature, we identified six possible candidate susceptibility genes for childhood asthma including ADCY2, DNAH5, KIF3A, PDE4B, PLAU, SPRR2B. To evaluate these genes, we compared the genotypes of 194 predominantly tagging SNPs in 790 asthmatic, allergic and non-allergic children. We found that SNPs in all six genes were nominally associated with asthma (p<0.05) in our discovery cohort and in three independent cohorts at either the SNP or gene level (p<0.05). Further, we determined that our selection approach was superior to random selection of genes either differentially expressed in asthmatics compared to controls (p = 0.0049) or selected based on the literature alone (p = 0.0049), substantiating the validity of our gene selection approach. Importantly, we observed that 7 of 9 SNPs in the KIF3A gene more than doubled the odds of asthma (OR = 2.3, p<0.0001) and increased the odds of allergic disease (OR = 1.8, p<0.008). Our data indicate that KIF3A rs7737031 (T-allele) has an asthma population attributable risk of 18.5%. The association between KIF3A rs7737031 and asthma was validated in 3 independent populations, further substantiating the validity of our gene selection approach. Conclusions/Significance Our study demonstrates that KIF3A, a member of the kinesin superfamily of microtubule associated motors that are important in the transport of protein complexes within cilia, is a novel candidate gene for childhood asthma. Polymorphisms in KIF3A may in part be responsible for poor mucus and/or allergen clearance from the airways. Furthermore, our study provides a promising framework for the identification and evaluation of novel candidate susceptibility genes. PMID:21912604

Comparative molecular analyses of select pH- and osmoregulatory genes in three freshwater crayfish Cherax quadricarinatus, C. destructor and C. cainii

PubMed Central

Pavasovic, Ana; Dammannagoda, Lalith K.; Mather, Peter B.; Prentis, Peter J.

2017-01-01

Systemic acid-base balance and osmotic/ionic regulation in decapod crustaceans are in part maintained by a set of transport-related enzymes such as carbonic anhydrase (CA), Na+/K+-ATPase (NKA), H+-ATPase (HAT), Na+/K+/2Cl− cotransporter (NKCC), Na+/Cl−/HCO\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}${}_{3}^{-}$\\end{document}3− cotransporter (NBC), Na+/H+ exchanger (NHE), Arginine kinase (AK), Sarcoplasmic Ca+2-ATPase (SERCA) and Calreticulin (CRT). We carried out a comparative molecular analysis of these genes in three commercially important yet eco-physiologically distinct freshwater crayfish, Cherax quadricarinatus, C. destructor and C. cainii, with the aim to identify mutations in these genes and determine if observed patterns of mutations were consistent with the action of natural selection. We also conducted a tissue-specific expression analysis of these genes across seven different organs, including gills, hepatopancreas, heart, kidney, liver, nerve and testes using NGS transcriptome data. The molecular analysis of the candidate genes revealed a high level of sequence conservation across the three Cherax sp. Hyphy analysis revealed that all candidate genes showed patterns of molecular variation consistent with neutral evolution. The tissue-specific expression analysis showed that 46% of candidate genes were expressed in all tissue types examined, while approximately 10% of candidate genes were only expressed in a single tissue type. The largest number of genes was observed in nerve (84%) and gills (78%) and the lowest in testes (66%). The tissue-specific expression analysis also revealed that most of the master genes regulating pH and osmoregulation (CA, NKA, HAT, NKCC, NBC, NHE) were expressed in all tissue types indicating an important physiological role for these genes outside of osmoregulation in other tissue types. The high level of sequence conservation observed in the candidate genes may be explained by the important role of these genes as well as potentially having a number of other basic physiological functions in different tissue types. PMID:28852583

Selection of Reliable Reference Genes for Gene Expression Studies of a Promising Oilseed Crop, Plukenetia volubilis, by Real-Time Quantitative PCR.

PubMed

Niu, Longjian; Tao, Yan-Bin; Chen, Mao-Sheng; Fu, Qiantang; Li, Chaoqiong; Dong, Yuling; Wang, Xiulan; He, Huiying; Xu, Zeng-Fu

2015-06-03

Real-time quantitative PCR (RT-qPCR) is a reliable and widely used method for gene expression analysis. The accuracy of the determination of a target gene expression level by RT-qPCR demands the use of appropriate reference genes to normalize the mRNA levels among different samples. However, suitable reference genes for RT-qPCR have not been identified in Sacha inchi (Plukenetia volubilis), a promising oilseed crop known for its polyunsaturated fatty acid (PUFA)-rich seeds. In this study, using RT-qPCR, twelve candidate reference genes were examined in seedlings and adult plants, during flower and seed development and for the entire growth cycle of Sacha inchi. Four statistical algorithms (delta cycle threshold (ΔCt), BestKeeper, geNorm, and NormFinder) were used to assess the expression stabilities of the candidate genes. The results showed that ubiquitin-conjugating enzyme (UCE), actin (ACT) and phospholipase A22 (PLA) were the most stable genes in Sacha inchi seedlings. For roots, stems, leaves, flowers, and seeds from adult plants, 30S ribosomal protein S13 (RPS13), cyclophilin (CYC) and elongation factor-1alpha (EF1α) were recommended as reference genes for RT-qPCR. During the development of reproductive organs, PLA, ACT and UCE were the optimal reference genes for flower development, whereas UCE, RPS13 and RNA polymerase II subunit (RPII) were optimal for seed development. Considering the entire growth cycle of Sacha inchi, UCE, ACT and EF1α were sufficient for the purpose of normalization. Our results provide useful guidelines for the selection of reliable reference genes for the normalization of RT-qPCR data for seedlings and adult plants, for reproductive organs, and for the entire growth cycle of Sacha inchi.

Evaluation and Selection of Candidate Reference Genes for Normalization of Quantitative RT-PCR in Withania somnifera (L.) Dunal

PubMed Central

Singh, Varinder; Kaul, Sunil C.; Wadhwa, Renu; Pati, Pratap Kumar

2015-01-01

Quantitative real-time PCR (qRT-PCR) is now globally used for accurate analysis of transcripts levels in plants. For reliable quantification of transcripts, identification of the best reference genes is a prerequisite in qRT-PCR analysis. Recently, Withania somnifera has attracted lot of attention due to its immense therapeutic potential. At present, biotechnological intervention for the improvement of this plant is being seriously pursued. In this background, it is important to have comprehensive studies on finding suitable reference genes for this high valued medicinal plant. In the present study, 11 candidate genes were evaluated for their expression stability under biotic (fungal disease), abiotic (wounding, salt, drought, heat and cold) stresses, in different plant tissues and in response to various plant growth regulators (methyl jasmonate, salicylic acid, abscisic acid). The data as analyzed by various software packages (geNorm, NormFinder, Bestkeeper and ΔCt method) suggested that cyclophilin (CYP) is a most stable gene under wounding, heat, methyl jasmonate, different tissues and all stress conditions. T-SAND was found to be a best reference gene for salt and salicylic acid (SA) treated samples, while 26S ribosomal RNA (26S), ubiquitin (UBQ) and beta-tubulin (TUB) were the most stably expressed genes under drought, biotic and cold treatment respectively. For abscisic acid (ABA) treated samples 18S-rRNA was found to stably expressed gene. Finally, the relative expression level of the three genes involved in the withanolide biosynthetic pathway was detected to validate the selection of reliable reference genes. The present work will significantly contribute to gene analysis studies in W. somnifera and facilitate in improving the quality of gene expression data in this plant as well as and other related plant species. PMID:25769035

Integrative Functional Genomics for Systems Genetics in GeneWeaver.org.

PubMed

Bubier, Jason A; Langston, Michael A; Baker, Erich J; Chesler, Elissa J

2017-01-01

The abundance of existing functional genomics studies permits an integrative approach to interpreting and resolving the results of diverse systems genetics studies. However, a major challenge lies in assembling and harmonizing heterogeneous data sets across species for facile comparison to the positional candidate genes and coexpression networks that come from systems genetic studies. GeneWeaver is an online database and suite of tools at www.geneweaver.org that allows for fast aggregation and analysis of gene set-centric data. GeneWeaver contains curated experimental data together with resource-level data such as GO annotations, MP annotations, and KEGG pathways, along with persistent stores of user entered data sets. These can be entered directly into GeneWeaver or transferred from widely used resources such as GeneNetwork.org. Data are analyzed using statistical tools and advanced graph algorithms to discover new relations, prioritize candidate genes, and generate function hypotheses. Here we use GeneWeaver to find genes common to multiple gene sets, prioritize candidate genes from a quantitative trait locus, and characterize a set of differentially expressed genes. Coupling a large multispecies repository curated and empirical functional genomics data to fast computational tools allows for the rapid integrative analysis of heterogeneous data for interpreting and extrapolating systems genetics results.

Stable Reference Gene Selection for RT-qPCR Analysis in Nonviruliferous and Viruliferous Frankliniella occidentalis.

PubMed

Yang, Chunxiao; Li, Hui; Pan, Huipeng; Ma, Yabin; Zhang, Deyong; Liu, Yong; Zhang, Zhanhong; Zheng, Changying; Chu, Dong

2015-01-01

Reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) is a reliable technique for measuring and evaluating gene expression during variable biological processes. To facilitate gene expression studies, normalization of genes of interest relative to stable reference genes is crucial. The western flower thrips Frankliniella occidentalis (Pergande) (Thysanoptera: Thripidae), the main vector of tomato spotted wilt virus (TSWV), is a destructive invasive species. In this study, the expression profiles of 11 candidate reference genes from nonviruliferous and viruliferous F. occidentalis were investigated. Five distinct algorithms, geNorm, NormFinder, BestKeeper, the ΔCt method, and RefFinder, were used to determine the performance of these genes. geNorm, NormFinder, BestKeeper, and RefFinder identified heat shock protein 70 (HSP70), heat shock protein 60 (HSP60), elongation factor 1 α, and ribosomal protein l32 (RPL32) as the most stable reference genes, and the ΔCt method identified HSP60, HSP70, RPL32, and heat shock protein 90 as the most stable reference genes. Additionally, two reference genes were sufficient for reliable normalization in nonviruliferous and viruliferous F. occidentalis. This work provides a foundation for investigating the molecular mechanisms of TSWV and F. occidentalis interactions.

A Strategy for Identifying Quantitative Trait Genes Using Gene Expression Analysis and Causal Analysis.

PubMed

Ishikawa, Akira

2017-11-27

Large numbers of quantitative trait loci (QTL) affecting complex diseases and other quantitative traits have been reported in humans and model animals. However, the genetic architecture of these traits remains elusive due to the difficulty in identifying causal quantitative trait genes (QTGs) for common QTL with relatively small phenotypic effects. A traditional strategy based on techniques such as positional cloning does not always enable identification of a single candidate gene for a QTL of interest because it is difficult to narrow down a target genomic interval of the QTL to a very small interval harboring only one gene. A combination of gene expression analysis and statistical causal analysis can greatly reduce the number of candidate genes. This integrated approach provides causal evidence that one of the candidate genes is a putative QTG for the QTL. Using this approach, I have recently succeeded in identifying a single putative QTG for resistance to obesity in mice. Here, I outline the integration approach and discuss its usefulness using my studies as an example.

GAPD and tubulin are suitable internal controls for qPCR analysis of oral squamous cell carcinoma cell lines.

PubMed

Campos, M S; Rodini, C O; Pinto-Júnior, D S; Nunes, F D

2009-02-01

The selection of housekeeping genes is critical for gene expression studies. To address this issue, four candidate housekeeping genes, including several commonly used ones, were investigated in oral squamous cell carcinoma cell lines. A simple quantitative RT-PCR approach was employed by comparing relative expression of the four candidate genes within two cancerous cell lines (HN6 and HN31) and one noncancerous cell line (HaCaT) treated or not with EGF and TGF-beta1. Data were analyzed using ANOVA followed by the NormFinder software program. On this basis, stability of the candidate housekeeping genes was ranked and non statistical differences were found using ANOVA test. On the other hand, the NormFinder was able to show that GAPD and TUBB presented the less variable results, representing appropriated housekeeping genes for the samples and conditions analyzed. In conclusion, this study suggests that the GAPD and the TUBB represent adequate normalizers for gene profiling studies in OSCC cell lines, covering, respectively, high and low expression levels genes.

Selection of reference genes for expression analysis in the entomophthoralean fungus Pandora neoaphidis.

PubMed

Chen, Chun; Xie, Tingna; Ye, Sudan; Jensen, Annette Bruun; Eilenberg, Jørgen

2016-01-01

The selection of suitable reference genes is crucial for accurate quantification of gene expression and can add to our understanding of host-pathogen interactions. To identify suitable reference genes in Pandora neoaphidis, an obligate aphid pathogenic fungus, the expression of three traditional candidate genes including 18S rRNA(18S), 28S rRNA(28S) and elongation factor 1 alpha-like protein (EF1), were measured by quantitative polymerase chain reaction at different developmental stages (conidia, conidia with germ tubes, short hyphae and elongated hyphae), and under different nutritional conditions. We calculated the expression stability of candidate reference genes using four algorithms including geNorm, NormFinder, BestKeeper and Delta Ct. The analysis results revealed that the comprehensive ranking of candidate reference genes from the most stable to the least stable was 18S (1.189), 28S (1.414) and EF1 (3). The 18S was, therefore, the most suitable reference gene for real-time RT-PCR analysis of gene expression under all conditions. These results will support further studies on gene expression in P. neoaphidis. Copyright © 2015 Sociedade Brasileira de Microbiologia. Published by Elsevier Editora Ltda. All rights reserved.

Novel Biomarker Candidates for Colorectal Cancer Metastasis: A Meta-analysis of In Vitro Studies

PubMed Central

Long, Nguyen Phuoc; Lee, Wun Jun; Huy, Nguyen Truong; Lee, Seul Ji; Park, Jeong Hill; Kwon, Sung Won

2016-01-01

Colorectal cancer (CRC) is one of the most common and lethal cancers. Although numerous studies have evaluated potential biomarkers for early diagnosis, current biomarkers have failed to reach an acceptable level of accuracy for distant metastasis. In this paper, we performed a gene set meta-analysis of in vitro microarray studies and combined the results from this study with previously published proteomic data to validate and suggest prognostic candidates for CRC metastasis. Two microarray data sets included found 21 significant genes. Of these significant genes, ALDOA, IL8 (CXCL8), and PARP4 had strong potential as prognostic candidates. LAMB2, MCM7, CXCL23A, SERPINA3, ABCA3, ALDH3A2, and POLR2I also have potential. Other candidates were more controversial, possibly because of the biologic heterogeneity of tumor cells, which is a major obstacle to predicting metastasis. In conclusion, we demonstrated a meta-analysis approach and successfully suggested ten biomarker candidates for future investigation. PMID:27688707

Novel Biomarker Candidates for Colorectal Cancer Metastasis: A Meta-analysis of In Vitro Studies.

PubMed

Long, Nguyen Phuoc; Lee, Wun Jun; Huy, Nguyen Truong; Lee, Seul Ji; Park, Jeong Hill; Kwon, Sung Won

2016-01-01

Colorectal cancer (CRC) is one of the most common and lethal cancers. Although numerous studies have evaluated potential biomarkers for early diagnosis, current biomarkers have failed to reach an acceptable level of accuracy for distant metastasis. In this paper, we performed a gene set meta-analysis of in vitro microarray studies and combined the results from this study with previously published proteomic data to validate and suggest prognostic candidates for CRC metastasis. Two microarray data sets included found 21 significant genes. Of these significant genes, ALDOA, IL8 (CXCL8), and PARP4 had strong potential as prognostic candidates. LAMB2, MCM7, CXCL23A, SERPINA3, ABCA3, ALDH3A2, and POLR2I also have potential. Other candidates were more controversial, possibly because of the biologic heterogeneity of tumor cells, which is a major obstacle to predicting metastasis. In conclusion, we demonstrated a meta-analysis approach and successfully suggested ten biomarker candidates for future investigation.

EXONSAMPLER: a computer program for genome-wide and candidate gene exon sampling for targeted next-generation sequencing.

PubMed

Cosart, Ted; Beja-Pereira, Albano; Luikart, Gordon

2014-11-01

The computer program EXONSAMPLER automates the sampling of thousands of exon sequences from publicly available reference genome sequences and gene annotation databases. It was designed to provide exon sequences for the efficient, next-generation gene sequencing method called exon capture. The exon sequences can be sampled by a list of gene name abbreviations (e.g. IFNG, TLR1), or by sampling exons from genes spaced evenly across chromosomes. It provides a list of genomic coordinates (a bed file), as well as a set of sequences in fasta format. User-adjustable parameters for collecting exon sequences include a minimum and maximum acceptable exon length, maximum number of exonic base pairs (bp) to sample per gene, and maximum total bp for the entire collection. It allows for partial sampling of very large exons. It can preferentially sample upstream (5 prime) exons, downstream (3 prime) exons, both external exons, or all internal exons. It is written in the Python programming language using its free libraries. We describe the use of EXONSAMPLER to collect exon sequences from the domestic cow (Bos taurus) genome for the design of an exon-capture microarray to sequence exons from related species, including the zebu cow and wild bison. We collected ~10% of the exome (~3 million bp), including 155 candidate genes, and ~16,000 exons evenly spaced genomewide. We prioritized the collection of 5 prime exons to facilitate discovery and genotyping of SNPs near upstream gene regulatory DNA sequences, which control gene expression and are often under natural selection. © 2014 John Wiley & Sons Ltd.

Frequency of ace, epa and elrA Genes in Clinical and Environmental Strains of Enterococcus faecalis.

PubMed

Lysakowska, Monika Eliza; Denys, Andrzej; Sienkiewicz, Monika

2012-12-01

Surface proteins play an important role in the pathogenesis of enterococcal infections. Some of them are candidates for a vaccine, e.g., the frequency of endocarditis in rats vaccinated with Ace protein was 75 % as 12 opposed to 100 % in those who weren't. However, there are other components of enterococcal cells, such as Epa antigens or internalin-like proteins, which may be used in the prophylaxis of infections caused by them. However, also other virulence factors and resistance to antibiotics are important during enterococcal infection. Therefore, the relevance of ace, epa, elrA, other virulence genes, as well as resistance to antibiotics was investigated. 161 Enterococcus faecalis strains isolated from teaching hospitals in Lodz, cultured according to standard microbiological methods, were investigated for the presence of genes encoding surface proteins by PCR. Results were analyzed with χ(2) test. The elrA gene was found in all clinical and environmental strains, the ace gene was also widespread among E. faecalis (96.9 %). Both tested epa genes were found in the majority of isolates (83.25 %). There was correlation between the presence of esp and ace genes (p = 0.046) as well as between epa and agg genes (p = 0.0094; χ(2) test). The presence of the genes encoding surface proteins investigated in our study in the great majority of isolates implies that they would appear to be required during E. faecalis infection. Therefore, they could be excellent targets in therapy of enterococcal infections or, as some studies show, candidates for vaccines.

Integrating De Novo Transcriptome Assembly and Cloning to Obtain Chicken Ovocleidin-17 Full-Length cDNA

PubMed Central

Ning, ZhongHua; Hincke, Maxwell T.; Yang, Ning; Hou, ZhuoCheng

2014-01-01

Efficiently obtaining full-length cDNA for a target gene is the key step for functional studies and probing genetic variations. However, almost all sequenced domestic animal genomes are not ‘finished’. Many functionally important genes are located in these gapped regions. It can be difficult to obtain full-length cDNA for which only partial amino acid/EST sequences exist. In this study we report a general pipeline to obtain full-length cDNA, and illustrate this approach for one important gene (Ovocleidin-17, OC-17) that is associated with chicken eggshell biomineralization. Chicken OC-17 is one of the best candidates to control and regulate the deposition of calcium carbonate in the calcified eggshell layer. OC-17 protein has been purified, sequenced, and has had its three-dimensional structure solved. However, researchers still cannot conduct OC-17 mRNA related studies because the mRNA sequence is unknown and the gene is absent from the current chicken genome. We used RNA-Seq to obtain the entire transcriptome of the adult hen uterus, and then conducted de novo transcriptome assembling with bioinformatics analysis to obtain candidate OC-17 transcripts. Based on this sequence, we used RACE and PCR cloning methods to successfully obtain the full-length OC-17 cDNA. Temporal and spatial OC-17 mRNA expression analyses were also performed to demonstrate that OC-17 is predominantly expressed in the adult hen uterus during the laying cycle and barely at immature developmental stages. Differential uterine expression of OC-17 was observed in hens laying eggs with weak versus strong eggshell, confirming its important role in the regulation of eggshell mineralization and providing a new tool for genetic selection for eggshell quality parameters. This study is the first one to report the full-length OC-17 cDNA sequence, and builds a foundation for OC-17 mRNA related studies. We provide a general method for biologists experiencing difficulty in obtaining candidate gene full-length cDNA sequences. PMID:24676480

Integrating de novo transcriptome assembly and cloning to obtain chicken Ovocleidin-17 full-length cDNA.

PubMed

Zhang, Quan; Liu, Long; Zhu, Feng; Ning, ZhongHua; Hincke, Maxwell T; Yang, Ning; Hou, ZhuoCheng

2014-01-01

Efficiently obtaining full-length cDNA for a target gene is the key step for functional studies and probing genetic variations. However, almost all sequenced domestic animal genomes are not 'finished'. Many functionally important genes are located in these gapped regions. It can be difficult to obtain full-length cDNA for which only partial amino acid/EST sequences exist. In this study we report a general pipeline to obtain full-length cDNA, and illustrate this approach for one important gene (Ovocleidin-17, OC-17) that is associated with chicken eggshell biomineralization. Chicken OC-17 is one of the best candidates to control and regulate the deposition of calcium carbonate in the calcified eggshell layer. OC-17 protein has been purified, sequenced, and has had its three-dimensional structure solved. However, researchers still cannot conduct OC-17 mRNA related studies because the mRNA sequence is unknown and the gene is absent from the current chicken genome. We used RNA-Seq to obtain the entire transcriptome of the adult hen uterus, and then conducted de novo transcriptome assembling with bioinformatics analysis to obtain candidate OC-17 transcripts. Based on this sequence, we used RACE and PCR cloning methods to successfully obtain the full-length OC-17 cDNA. Temporal and spatial OC-17 mRNA expression analyses were also performed to demonstrate that OC-17 is predominantly expressed in the adult hen uterus during the laying cycle and barely at immature developmental stages. Differential uterine expression of OC-17 was observed in hens laying eggs with weak versus strong eggshell, confirming its important role in the regulation of eggshell mineralization and providing a new tool for genetic selection for eggshell quality parameters. This study is the first one to report the full-length OC-17 cDNA sequence, and builds a foundation for OC-17 mRNA related studies. We provide a general method for biologists experiencing difficulty in obtaining candidate gene full-length cDNA sequences.

Identification of Novel Associations of Candidate Genes with Resistance to Late Blight in Solanum tuberosum Group Phureja

PubMed Central

Álvarez, María F.; Angarita, Myrian; Delgado, María C.; García, Celsa; Jiménez-Gomez, José; Gebhardt, Christiane; Mosquera, Teresa

2017-01-01

The genetic basis of quantitative disease resistance has been studied in crops for several decades as an alternative to R gene mediated resistance. The most important disease in the potato crop is late blight, caused by the oomycete Phytophthora infestans. Quantitative disease resistance (QDR), as any other quantitative trait in plants, can be genetically mapped to understand the genetic architecture. Association mapping using DNA-based markers has been implemented in many crops to dissect quantitative traits. We used an association mapping approach with candidate genes to identify the first genes associated with quantitative resistance to late blight in Solanum tuberosum Group Phureja. Twenty-nine candidate genes were selected from a set of genes that were differentially expressed during the resistance response to late blight in tetraploid European potato cultivars. The 29 genes were amplified and sequenced in 104 accessions of S. tuberosum Group Phureja from Latin America. We identified 238 SNPs in the selected genes and tested them for association with resistance to late blight. The phenotypic data were obtained under field conditions by determining the area under disease progress curve (AUDPC) in two seasons and in two locations. Two genes were associated with QDR to late blight, a potato homolog of thylakoid lumen 15 kDa protein (StTL15A) and a stem 28 kDa glycoprotein (StGP28). Key message: A first association mapping experiment was conducted in Solanum tuberosum Group Phureja germplasm, which identified among 29 candidates two genes associated with quantitative resistance to late blight. PMID:28674545

Photoreceptor dysplasia (pd) in miniature schnauzer dogs: evaluation of candidate genes by molecular genetic analysis.

PubMed

Zhang, Q; Baldwin, V J; Acland, G M; Parshall, C J; Haskel, J; Aguirre, G D; Ray, K

1999-01-01

Photoreceptor dysplasia (pd) is one of a group of at least six distinct autosomal and one X-linked retinal disorders identified in dogs which are collectively known as progressive retinal atrophy (PRA). It is an early onset retinal disease identified in miniature schnauzer dogs, and pedigree analysis and breeding studies have established autosomal recessive inheritance of the disease. Using a gene-based approach, a number of retina-expressed genes, including some members of the phototransduction pathway, have been causally implicated in retinal diseases of humans and other animals. Here we examined seven such potential candidate genes (opsin, RDS/peripherin, ROM1, rod cGMP-gated cation channel alpha-subunit, and three subunits of transducin) for their causal association with the pd locus by testing segregation of intragenic markers with the disease locus, or, in the absence of informative polymorphisms, sequencing of the coding regions of the genes. Based on these results, we have conclusively excluded four photoreceptor-specific genes as candidates for pd by linkage analysis. For three other photoreceptor-specific genes, we did not find any mutation in the coding sequences of the genes and have excluded them provisionally. Formal exclusion would require investigation of the levels of expression of the candidate genes in pd-affected dogs relative to age-matched controls. At present we are building suitable informative pedigrees for the disease locus with a sufficient number of meiosis to be useful for genomewide screening. This should identify markers linked to the disease locus and eventually permit progress toward the identification of the photoreceptor dysplasia gene and the disease-causing mutation.

Identification of Novel Associations of Candidate Genes with Resistance to Late Blight in Solanum tuberosum Group Phureja.

PubMed

Álvarez, María F; Angarita, Myrian; Delgado, María C; García, Celsa; Jiménez-Gomez, José; Gebhardt, Christiane; Mosquera, Teresa

2017-01-01

The genetic basis of quantitative disease resistance has been studied in crops for several decades as an alternative to R gene mediated resistance. The most important disease in the potato crop is late blight, caused by the oomycete Phytophthora infestans. Quantitative disease resistance (QDR), as any other quantitative trait in plants, can be genetically mapped to understand the genetic architecture. Association mapping using DNA-based markers has been implemented in many crops to dissect quantitative traits. We used an association mapping approach with candidate genes to identify the first genes associated with quantitative resistance to late blight in Solanum tuberosum Group Phureja. Twenty-nine candidate genes were selected from a set of genes that were differentially expressed during the resistance response to late blight in tetraploid European potato cultivars. The 29 genes were amplified and sequenced in 104 accessions of S. tuberosum Group Phureja from Latin America. We identified 238 SNPs in the selected genes and tested them for association with resistance to late blight. The phenotypic data were obtained under field conditions by determining the area under disease progress curve (AUDPC) in two seasons and in two locations. Two genes were associated with QDR to late blight, a potato homolog of thylakoid lumen 15 kDa protein ( StTL15A ) and a stem 28 kDa glycoprotein ( StGP28 ). Key message : A first association mapping experiment was conducted in Solanum tuberosum Group Phureja germplasm, which identified among 29 candidates two genes associated with quantitative resistance to late blight.

A transposon-based genetic screen in mice identifies genes altered in colorectal cancer.

PubMed

Starr, Timothy K; Allaei, Raha; Silverstein, Kevin A T; Staggs, Rodney A; Sarver, Aaron L; Bergemann, Tracy L; Gupta, Mihir; O'Sullivan, M Gerard; Matise, Ilze; Dupuy, Adam J; Collier, Lara S; Powers, Scott; Oberg, Ann L; Asmann, Yan W; Thibodeau, Stephen N; Tessarollo, Lino; Copeland, Neal G; Jenkins, Nancy A; Cormier, Robert T; Largaespada, David A

2009-03-27

Human colorectal cancers (CRCs) display a large number of genetic and epigenetic alterations, some of which are causally involved in tumorigenesis (drivers) and others that have little functional impact (passengers). To help distinguish between these two classes of alterations, we used a transposon-based genetic screen in mice to identify candidate genes for CRC. Mice harboring mutagenic Sleeping Beauty (SB) transposons were crossed with mice expressing SB transposase in gastrointestinal tract epithelium. Most of the offspring developed intestinal lesions, including intraepithelial neoplasia, adenomas, and adenocarcinomas. Analysis of over 16,000 transposon insertions identified 77 candidate CRC genes, 60 of which are mutated and/or dysregulated in human CRC and thus are most likely to drive tumorigenesis. These genes include APC, PTEN, and SMAD4. The screen also identified 17 candidate genes that had not previously been implicated in CRC, including POLI, PTPRK, and RSPO2.

Utilization of gene mapping and candidate gene mutation screening for diagnosing clinically equivocal conditions: a Norrie disease case study.

PubMed

Chini, Vasiliki; Stambouli, Danai; Nedelea, Florina Mihaela; Filipescu, George Alexandru; Mina, Diana; Kambouris, Marios; El-Shantil, Hatem

2014-06-01

Prenatal diagnosis was requested for an undiagnosed eye disease showing X-linked inheritance in a family. No medical records existed for the affected family members. Mapping of the X chromosome and candidate gene mutation screening identified a c.C267A[p.F89L] mutation in NPD previously described as possibly causing Norrie disease. The detection of the c.C267A[p.F89L] variant in another unrelated family confirms the pathogenic nature of the mutation for the Norrie disease phenotype. Gene mapping, haplotype analysis, and candidate gene screening have been previously utilized in research applications but were applied here in a diagnostic setting due to the scarcity of available clinical information. The clinical diagnosis and mutation identification were critical for providing proper genetic counseling and prenatal diagnosis for this family.

Diversifying selection in the wheat stem rust fungus acts predominantly on pathogen-associated gene families and reveals candidate effectors

PubMed Central

Sperschneider, Jana; Ying, Hua; Dodds, Peter N.; Gardiner, Donald M.; Upadhyaya, Narayana M.; Singh, Karam B.; Manners, John M.; Taylor, Jennifer M.

2014-01-01

Plant pathogens cause severe losses to crop plants and threaten global food production. One striking example is the wheat stem rust fungus, Puccinia graminis f. sp. tritici, which can rapidly evolve new virulent pathotypes in response to resistant host lines. Like several other filamentous fungal and oomycete plant pathogens, its genome features expanded gene families that have been implicated in host-pathogen interactions, possibly encoding effector proteins that interact directly with target host defense proteins. Previous efforts to understand virulence largely relied on the prediction of secreted, small and cysteine-rich proteins as candidate effectors and thus delivered an overwhelming number of candidates. Here, we implement an alternative analysis strategy that uses the signal of adaptive evolution as a line of evidence for effector function, combined with comparative information and expression data. We demonstrate that in planta up-regulated genes that are rapidly evolving are found almost exclusively in pathogen-associated gene families, affirming the impact of host-pathogen co-evolution on genome structure and the adaptive diversification of specialized gene families. In particular, we predict 42 effector candidates that are conserved only across pathogens, induced during infection and rapidly evolving. One of our top candidates has recently been shown to induce genotype-specific hypersensitive cell death in wheat. This shows that comparative genomics incorporating the evolutionary signal of adaptation is powerful for predicting effector candidates for laboratory verification. Our system can be applied to a wide range of pathogens and will give insight into host-pathogen dynamics, ultimately leading to progress in strategies for disease control. PMID:25225496

Phylogenomic analysis demonstrates a pattern of rare and ancient horizontal gene transfer between plants and fungi.

PubMed

Richards, Thomas A; Soanes, Darren M; Foster, Peter G; Leonard, Guy; Thornton, Christopher R; Talbot, Nicholas J

2009-07-01

Horizontal gene transfer (HGT) describes the transmission of genetic material across species boundaries and is an important evolutionary phenomenon in the ancestry of many microbes. The role of HGT in plant evolutionary history is, however, largely unexplored. Here, we compare the genomes of six plant species with those of 159 prokaryotic and eukaryotic species and identify 1689 genes that show the highest similarity to corresponding genes from fungi. We constructed a phylogeny for all 1689 genes identified and all homolog groups available from the rice (Oryza sativa) genome (3177 gene families) and used these to define 14 candidate plant-fungi HGT events. Comprehensive phylogenetic analyses of these 14 data sets, using methods that account for site rate heterogeneity, demonstrated support for nine HGT events, demonstrating an infrequent pattern of HGT between plants and fungi. Five HGTs were fungi-to-plant transfers and four were plant-to-fungi HGTs. None of the fungal-to-plant HGTs involved angiosperm recipients. These results alter the current view of organismal barriers to HGT, suggesting that phagotrophy, the consumption of a whole cell by another, is not necessarily a prerequisite for HGT between eukaryotes. Putative functional annotation of the HGT candidate genes suggests that two fungi-to-plant transfers have added phenotypes important for life in a soil environment. Our study suggests that genetic exchange between plants and fungi is exceedingly rare, particularly among the angiosperms, but has occurred during their evolutionary history and added important metabolic traits to plant lineages.

Absolute Quantitation of DNA Methylation of 28 Candidate Genes in Prostate Cancer Using Pyrosequencing

PubMed Central

Vasiljeviš, Nataڑa; Wu, Keqiang; Brentnall, Adam R.; Kim, Dae Cheol; Thorat, Mangesh A.; Kudahetti, Sakunthala C.; Mao, Xueying; Xue, Liyan; Yu, Yongwei; Shaw, Greg L.; Beltran, Luis; Lu, Yong-Jie; Berney, Daniel M.; Cuzick, Jack; Lorincz, Attila T.

2011-01-01

Aberrant DNA methylation plays a pivotal role in carcinogenesis and its mapping is likely to provide biomarkers for improved diagnostic and risk assessment in prostate cancer (PCa). We quantified and compared absolute methylation levels among 28 candidate genes in 48 PCa and 29 benign prostate hyperplasia (BPH) samples using the pyrosequencing (PSQ) method to identify genes with diagnostic and prognostic potential. RARB, HIN1, BCL2, GSTP1, CCND2, EGFR5, APC, RASSF1A, MDR1, NKX2-5, CDH13, DPYS, PTGS2, EDNRB, MAL, PDLIM4, HLAa, ESR1 and TIG1 were highly methylated in PCa compared to BPH (p < 0.001), while SERPINB5, CDH1, TWIST1, DAPK1, THRB, MCAM, SLIT2, CDKN2a and SFN were not. RARB methylation above 21% completely distinguished PCa from BPH. Separation based on methylation level of SFN, SLIT2 and SERPINB5 distinguished low and high Gleason score cancers, e.g. SFN and SERPINB5 together correctly classified 81% and 77% of high and low Gleason score cancers respectively. Several genes including CDH1 previously reported as methylation markers in PCa were not confirmed in our study. Increasing age was positively associated with gene methylation (p < 0.0001). Accurate quantitative measurement of gene methylation in PCa appears promising and further validation of genes like RARB, HIN1, BCL2, APC and GSTP1 is warranted for diagnostic potential and SFN, SLIT2 and SERPINB5 for prognostic potential. PMID:21694441

Integrating microarray analysis and the soybean genome to understand the soybeans iron deficiency response

PubMed Central

2009-01-01

Background Soybeans grown in the upper Midwestern United States often suffer from iron deficiency chlorosis, which results in yield loss at the end of the season. To better understand the effect of iron availability on soybean yield, we identified genes in two near isogenic lines with changes in expression patterns when plants were grown in iron sufficient and iron deficient conditions. Results Transcriptional profiles of soybean (Glycine max, L. Merr) near isogenic lines Clark (PI548553, iron efficient) and IsoClark (PI547430, iron inefficient) grown under Fe-sufficient and Fe-limited conditions were analyzed and compared using the Affymetrix® GeneChip® Soybean Genome Array. There were 835 candidate genes in the Clark (PI548553) genotype and 200 candidate genes in the IsoClark (PI547430) genotype putatively involved in soybean's iron stress response. Of these candidate genes, fifty-eight genes in the Clark genotype were identified with a genetic location within known iron efficiency QTL and 21 in the IsoClark genotype. The arrays also identified 170 single feature polymorphisms (SFPs) specific to either Clark or IsoClark. A sliding window analysis of the microarray data and the 7X genome assembly coupled with an iterative model of the data showed the candidate genes are clustered in the genome. An analysis of 5' untranslated regions in the promoter of candidate genes identified 11 conserved motifs in 248 differentially expressed genes, all from the Clark genotype, representing 129 clusters identified earlier, confirming the cluster analysis results. Conclusion These analyses have identified the first genes with expression patterns that are affected by iron stress and are located within QTL specific to iron deficiency stress. The genetic location and promoter motif analysis results support the hypothesis that the differentially expressed genes are co-regulated. The combined results of all analyses lead us to postulate iron inefficiency in soybean is a result of a mutation in a transcription factor(s), which controls the expression of genes required in inducing an iron stress response. PMID:19678937

Candidate Proteins, Metabolites and Transcripts in the Biomarkers for Spinal Muscular Atrophy (BforSMA) Clinical Study

PubMed Central

Finkel, Richard S.; Crawford, Thomas O.; Swoboda, Kathryn J.; Kaufmann, Petra; Juhasz, Peter; Li, Xiaohong; Guo, Yu; Li, Rebecca H.; Trachtenberg, Felicia; Forrest, Suzanne J.; Kobayashi, Dione T.; Chen, Karen S.; Joyce, Cynthia L.; Plasterer, Thomas

2012-01-01

Background Spinal Muscular Atrophy (SMA) is a neurodegenerative motor neuron disorder resulting from a homozygous mutation of the survival of motor neuron 1 (SMN1) gene. The gene product, SMN protein, functions in RNA biosynthesis in all tissues. In humans, a nearly identical gene, SMN2, rescues an otherwise lethal phenotype by producing a small amount of full-length SMN protein. SMN2 copy number inversely correlates with disease severity. Identifying other novel biomarkers could inform clinical trial design and identify novel therapeutic targets. Objective: To identify novel candidate biomarkers associated with disease severity in SMA using unbiased proteomic, metabolomic and transcriptomic approaches. Materials and Methods: A cross-sectional single evaluation was performed in 108 children with genetically confirmed SMA, aged 2–12 years, manifesting a broad range of disease severity and selected to distinguish factors associated with SMA type and present functional ability independent of age. Blood and urine specimens from these and 22 age-matched healthy controls were interrogated using proteomic, metabolomic and transcriptomic discovery platforms. Analyte associations were evaluated against a primary measure of disease severity, the Modified Hammersmith Functional Motor Scale (MHFMS) and to a number of secondary clinical measures. Results A total of 200 candidate biomarkers correlate with MHFMS scores: 97 plasma proteins, 59 plasma metabolites (9 amino acids, 10 free fatty acids, 12 lipids and 28 GC/MS metabolites) and 44 urine metabolites. No transcripts correlated with MHFMS. Discussion In this cross-sectional study, “BforSMA” (Biomarkers for SMA), candidate protein and metabolite markers were identified. No transcript biomarker candidates were identified. Additional mining of this rich dataset may yield important insights into relevant SMA-related pathophysiology and biological network associations. Additional prospective studies are needed to confirm these findings, demonstrate sensitivity to change with disease progression, and assess potential impact on clinical trial design. Trial Registry Clinicaltrials.gov NCT00756821. PMID:22558154

Dissecting the Molecular Mechanism of RhoC GTPase Expression in the Normal and Malignant Breast

DTIC Science & Technology

2010-09-01

Headquarters Services , Directorate for Information Operations and Reports (0704-0188), 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202- 4302...transcriptome and categorized as (i) mapping to same gene, (ii) mapping to different genes (chimera candidates), (iii) nonmapping, (iv) mitochondrial, (v) quality ...mitochondrial, (iv) quality control, (v) chimera can- didates, and (vi) nonmapping. Chimera candidates and nonmapping categories were used for gene fusion

Haploinsufficiency of TAB2 Causes Congenital Heart Defects in Humans

PubMed Central

Thienpont, Bernard; Zhang, Litu; Postma, Alex V.; Breckpot, Jeroen; Tranchevent, Léon-Charles; Van Loo, Peter; Møllgård, Kjeld; Tommerup, Niels; Bache, Iben; Tümer, Zeynep; van Engelen, Klaartje; Menten, Björn; Mortier, Geert; Waggoner, Darrel; Gewillig, Marc; Moreau, Yves; Devriendt, Koen; Larsen, Lars Allan

2010-01-01

Congenital heart defects (CHDs) are the most common major developmental anomalies and the most frequent cause for perinatal mortality, but their etiology remains often obscure. We identified a locus for CHDs on 6q24-q25. Genotype-phenotype correlations in 12 patients carrying a chromosomal deletion on 6q delineated a critical 850 kb region on 6q25.1 harboring five genes. Bioinformatics prioritization of candidate genes in this locus for a role in CHDs identified the TGF-β-activated kinase 1/MAP3K7 binding protein 2 gene (TAB2) as the top-ranking candidate gene. A role for this candidate gene in cardiac development was further supported by its conserved expression in the developing human and zebrafish heart. Moreover, a critical, dosage-sensitive role during development was demonstrated by the cardiac defects observed upon titrated knockdown of tab2 expression in zebrafish embryos. To definitively confirm the role of this candidate gene in CHDs, we performed mutation analysis of TAB2 in 402 patients with a CHD, which revealed two evolutionarily conserved missense mutations. Finally, a balanced translocation was identified, cosegregating with familial CHD. Mapping of the breakpoints demonstrated that this translocation disrupts TAB2. Taken together, these data clearly demonstrate a role for TAB2 in human cardiac development. PMID:20493459

“Soldier's Heart”: A Genetic Basis for Elevated Cardiovascular Disease Risk Associated with Post-traumatic Stress Disorder

PubMed Central

Pollard, Harvey B.; Shivakumar, Chittari; Starr, Joshua; Eidelman, Ofer; Jacobowitz, David M.; Dalgard, Clifton L.; Srivastava, Meera; Wilkerson, Matthew D.; Stein, Murray B.; Ursano, Robert J.

2016-01-01

“Soldier's Heart,” is an American Civil War term linking post-traumatic stress disorder (PTSD) with increased propensity for cardiovascular disease (CVD). We have hypothesized that there might be a quantifiable genetic basis for this linkage. To test this hypothesis we identified a comprehensive set of candidate risk genes for PTSD, and tested whether any were also independent risk genes for CVD. A functional analysis algorithm was used to identify associated signaling networks. We identified 106 PTSD studies that report one or more polymorphic variants in 87 candidate genes in 83,463 subjects and controls. The top upstream drivers for these PTSD risk genes are predicted to be the glucocorticoid receptor (NR3C1) and Tumor Necrosis Factor alpha (TNFA). We find that 37 of the PTSD candidate risk genes are also candidate independent risk genes for CVD. The association between PTSD and CVD is significant by Fisher's Exact Test (P = 3 × 10−54). We also find 15 PTSD risk genes that are independently associated with Type 2 Diabetes Mellitus (T2DM; also significant by Fisher's Exact Test (P = 1.8 × 10−16). Our findings offer quantitative evidence for a genetic link between post-traumatic stress and cardiovascular disease, Computationally, the common mechanism for this linkage between PTSD and CVD is innate immunity and NFκB-mediated inflammation. PMID:27721742

"Soldier's Heart": A Genetic Basis for Elevated Cardiovascular Disease Risk Associated with Post-traumatic Stress Disorder.

PubMed

Pollard, Harvey B; Shivakumar, Chittari; Starr, Joshua; Eidelman, Ofer; Jacobowitz, David M; Dalgard, Clifton L; Srivastava, Meera; Wilkerson, Matthew D; Stein, Murray B; Ursano, Robert J

2016-01-01

"Soldier's Heart," is an American Civil War term linking post-traumatic stress disorder (PTSD) with increased propensity for cardiovascular disease (CVD). We have hypothesized that there might be a quantifiable genetic basis for this linkage. To test this hypothesis we identified a comprehensive set of candidate risk genes for PTSD, and tested whether any were also independent risk genes for CVD. A functional analysis algorithm was used to identify associated signaling networks. We identified 106 PTSD studies that report one or more polymorphic variants in 87 candidate genes in 83,463 subjects and controls. The top upstream drivers for these PTSD risk genes are predicted to be the glucocorticoid receptor (NR3C1) and Tumor Necrosis Factor alpha (TNFA). We find that 37 of the PTSD candidate risk genes are also candidate independent risk genes for CVD. The association between PTSD and CVD is significant by Fisher's Exact Test ( P = 3 × 10 -54 ). We also find 15 PTSD risk genes that are independently associated with Type 2 Diabetes Mellitus (T2DM; also significant by Fisher's Exact Test ( P = 1.8 × 10 -16 ). Our findings offer quantitative evidence for a genetic link between post-traumatic stress and cardiovascular disease, Computationally, the common mechanism for this linkage between PTSD and CVD is innate immunity and NFκB-mediated inflammation.

OVA: integrating molecular and physical phenotype data from multiple biomedical domain ontologies with variant filtering for enhanced variant prioritization.

PubMed

Antanaviciute, Agne; Watson, Christopher M; Harrison, Sally M; Lascelles, Carolina; Crinnion, Laura; Markham, Alexander F; Bonthron, David T; Carr, Ian M

2015-12-01

Exome sequencing has become a de facto standard method for Mendelian disease gene discovery in recent years, yet identifying disease-causing mutations among thousands of candidate variants remains a non-trivial task. Here we describe a new variant prioritization tool, OVA (ontology variant analysis), in which user-provided phenotypic information is exploited to infer deeper biological context. OVA combines a knowledge-based approach with a variant-filtering framework. It reduces the number of candidate variants by considering genotype and predicted effect on protein sequence, and scores the remainder on biological relevance to the query phenotype.We take advantage of several ontologies in order to bridge knowledge across multiple biomedical domains and facilitate computational analysis of annotations pertaining to genes, diseases, phenotypes, tissues and pathways. In this way, OVA combines information regarding molecular and physical phenotypes and integrates both human and model organism data to effectively prioritize variants. By assessing performance on both known and novel disease mutations, we show that OVA performs biologically meaningful candidate variant prioritization and can be more accurate than another recently published candidate variant prioritization tool. OVA is freely accessible at http://dna2.leeds.ac.uk:8080/OVA/index.jsp. Supplementary data are available at Bioinformatics online. umaan@leeds.ac.uk. © The Author 2015. Published by Oxford University Press.

Candidate gene association mapping for winter survival and spring regrowth in perennial ryegrass

USDA-ARS?s Scientific Manuscript database

Perennial ryegrass (Lolium perenne L.) is a widely cultivated cool-season grass species because of its high quality for forage and turf. Susceptibility to freezing damage limits its further use in temperate zones. The objective of this study was to identify candidate genes significantly associated w...

Mapping Gene Associations in Human Mitochondria using Clinical Disease Phenotypes

PubMed Central

Scharfe, Curt; Lu, Henry Horng-Shing; Neuenburg, Jutta K.; Allen, Edward A.; Li, Guan-Cheng; Klopstock, Thomas; Cowan, Tina M.; Enns, Gregory M.; Davis, Ronald W.

2009-01-01

Nuclear genes encode most mitochondrial proteins, and their mutations cause diverse and debilitating clinical disorders. To date, 1,200 of these mitochondrial genes have been recorded, while no standardized catalog exists of the associated clinical phenotypes. Such a catalog would be useful to develop methods to analyze human phenotypic data, to determine genotype-phenotype relations among many genes and diseases, and to support the clinical diagnosis of mitochondrial disorders. Here we establish a clinical phenotype catalog of 174 mitochondrial disease genes and study associations of diseases and genes. Phenotypic features such as clinical signs and symptoms were manually annotated from full-text medical articles and classified based on the hierarchical MeSH ontology. This classification of phenotypic features of each gene allowed for the comparison of diseases between different genes. In turn, we were then able to measure the phenotypic associations of disease genes for which we calculated a quantitative value that is based on their shared phenotypic features. The results showed that genes sharing more similar phenotypes have a stronger tendency for functional interactions, proving the usefulness of phenotype similarity values in disease gene network analysis. We then constructed a functional network of mitochondrial genes and discovered a higher connectivity for non-disease than for disease genes, and a tendency of disease genes to interact with each other. Utilizing these differences, we propose 168 candidate genes that resemble the characteristic interaction patterns of mitochondrial disease genes. Through their network associations, the candidates are further prioritized for the study of specific disorders such as optic neuropathies and Parkinson disease. Most mitochondrial disease phenotypes involve several clinical categories including neurologic, metabolic, and gastrointestinal disorders, which might indicate the effects of gene defects within the mitochondrial system. The accompanying knowledgebase (http://www.mitophenome.org/) supports the study of clinical diseases and associated genes. PMID:19390613

Novel genes on rat chromosome 10 are linked to body fat mass, preadipocyte number and adipocyte size.

PubMed

Weingarten, A; Turchetti, L; Krohn, K; Klöting, I; Kern, M; Kovacs, P; Stumvoll, M; Blüher, M; Klöting, N

2016-12-01

The genetic architecture of obesity is multifactorial. We have previously identified a quantitative trait locus (QTL) on rat chromosome 10 in a F2 cross of Wistar Ottawa Karlsburg (WOKW) and Dark Agouti (DA) rats responsible for obesity-related traits. The QTL was confirmed in congenic DA.WOKW10 rats. To pinpoint the region carrying causal genes, we established two new subcongenic lines, L1 and L2, with smaller refined segments of chromosome 10 to identify novel candidate genes. All lines were extensively characterized under different diet conditions. We employed transcriptome analysis in visceral adipose tissue (VAT) by RNA-Seq technology to identify potential underlying genes in the segregating regions. Three candidate genes were measured in human paired samples of VAT and subcutaneous (SC) AT (SAT) (N=304) individuals with a wide range of body weight and glucose homeostasis parameters. DA.WOKW and L1 subcongenic lines were protected against body fat gain under high-fat diet (HFD), whereas L2 and DA had significantly more body fat after high-fat feeding. Interestingly, adipocyte size distribution in SAT and epigonadal AT of L1 subcongenic rats did not undergo typical ballooning under HFD and the number of preadipocytes in AT was significantly elevated in L2 compared with L1 and parental rats. Transcriptome analysis identified three candidate genes in VAT on rat chromosome 10. In humans, these candidate genes were differentially expressed between SAT and VAT. Moreover, HID1 mRNA significantly correlates with parameters of obesity and glucose metabolism. Our data suggest novel candidate genes for obesity that map on rat chromosome 10 in an interval 102.2-104.7 Mb and are strongly associated with body fat mass regulation, preadipocyte number and adipocyte size in rats. Among those genes, AT head involution defective (HID1) mRNA expression may be relevant for human fat distribution and glucose homeostasis.

Novel Antigen Identification Method for Discovery of Protective Malaria Antigens by Rapid Testing of DNA Vaccines Encoding Exons from the Parasite Genome

PubMed Central

Haddad, Diana; Bilcikova, Erika; Witney, Adam A.; Carlton, Jane M.; White, Charles E.; Blair, Peter L.; Chattopadhyay, Rana; Russell, Joshua; Abot, Esteban; Charoenvit, Yupin; Aguiar, Joao C.; Carucci, Daniel J.; Weiss, Walter R.

2004-01-01

We describe a novel approach for identifying target antigens for preerythrocytic malaria vaccines. Our strategy is to rapidly test hundreds of DNA vaccines encoding exons from the Plasmodium yoelii yoelii genomic sequence. In this antigen identification method, we measure reduction in parasite burden in the liver after sporozoite challenge in mice. Orthologs of protective P. y. yoelii genes can then be identified in the genomic databases of Plasmodium falciparum and Plasmodium vivax and investigated as candidate antigens for a human vaccine. A pilot study to develop the antigen identification method approach used 192 P. y. yoelii exons from genes expressed during the sporozoite stage of the life cycle. A total of 182 (94%) exons were successfully cloned into a DNA immunization vector with the Gateway cloning technology. To assess immunization strategies, mice were vaccinated with 19 of the new DNA plasmids in addition to the well-characterized protective plasmid encoding P. y. yoelii circumsporozoite protein. Single plasmid immunization by gene gun identified a novel vaccine target antigen which decreased liver parasite burden by 95% and which has orthologs in P. vivax and P. knowlesi but not P. falciparum. Intramuscular injection of DNA plasmids produced a different pattern of protective responses from those seen with gene gun immunization. Intramuscular immunization with plasmid pools could reduce liver parasite burden in mice despite the fact that none of the plasmids was protective when given individually. We conclude that high-throughput cloning of exons into DNA vaccines and their screening is feasible and can rapidly identify new malaria vaccine candidate antigens. PMID:14977966

[Linkage analysis of a family with familial hypertriglyceridemia].

PubMed

Tang, Xin; Lin, Ying; Liu, Bing; Ma, Shi; Yang, Yang; Yang, Zheng-lin

2009-10-01

To perform linkage analysis and mutation screening in a Chinese family with familial hpertriglyceridemia (FHTG). Thirty-two family members including 12 hypertriglyceridemia patients participated in the study. Genotyping and haplotype analysis for 22 subjects were performed using short tandem repeat (STR) microsatellite polymorphism markers on 16 candidate genes and/or loci related to lipid metabolism. Two of the sixteen known candidate genes, APOA2 and USF1 were screened for mutation by direct DNA sequencing. No linkage was found between the candidate genes/loci of APOA5, LIPI, RP1, APOC2, ABC1, LMF1, APOA1-APOC3-APOA4, LPL, APOB, CETP, LCAT, LDLR, APOE and the phenotype in this family. The two-point Lod scores (theta =0) were all less than-1.0 for all the markers tested. Linkage analysis suggested linkage to chromosome 1q23.3-24.2 between the disease phenotype and STR marker D1S194 with a two-point maximum Lod score of 2.44 at theta =0. Fine mapping indicated that the disease gene was localized to a 5.87 cM interval between D1S104 and D1S196. No disease-causing mutation was detected in the APOA2 and USF1 genes. The above mentioned candidate genes were excluded as the disease causing genes for this family. The results implied that there might be a novel gene/locus for FHTG on chromosome 1q23.3-1q24.2.

In silico identification of genetically attenuated vaccine candidate genes for Plasmodium liver stage.

PubMed

Kumar, Hirdesh; Frischknecht, Friedrich; Mair, Gunnar R; Gomes, James

2015-12-01

Genetically attenuated parasites (GAPs) that lack genes essential for the liver stage of the malaria parasite, and therefore cause developmental arrest, have been developed as live vaccines in rodent malaria models and recently been tested in humans. The genes targeted for deletion were often identified by trial and error. Here we present a systematic gene - protein and transcript - expression analyses of several Plasmodium species with the aim to identify candidate genes for the generation of novel GAPs. With a lack of liver stage expression data for human malaria parasites, we used data available for liver stage development of Plasmodium yoelii, a rodent malaria model, to identify proteins expressed in the liver stage but absent from blood stage parasites. An orthology-based search was then employed to identify orthologous proteins in the human malaria parasite Plasmodium falciparum resulting in a total of 310 genes expressed in the liver stage but lacking evidence of protein expression in blood stage parasites. Among these 310 possible GAP candidates, we further studied Plasmodium liver stage proteins by phyletic distribution and functional domain analyses and shortlisted twenty GAP-candidates; these are: fabB/F, fabI, arp, 3 genes encoding subunits of the PDH complex, dnaJ, urm1, rS5, ancp, mcp, arh, gk, lisp2, valS, palm, and four conserved Plasmodium proteins of unknown function. Parasites lacking one or several of these genes might yield new attenuated malaria parasites for experimental vaccination studies. Copyright © 2015 Elsevier B.V. All rights reserved.

Genome-Wide Association Study of Seed Dormancy and the Genomic Consequences of Improvement Footprints in Rice (Oryza sativa L.)

PubMed Central

Lu, Qing; Niu, Xiaojun; Zhang, Mengchen; Wang, Caihong; Xu, Qun; Feng, Yue; Yang, Yaolong; Wang, Shan; Yuan, Xiaoping; Yu, Hanyong; Wang, Yiping; Chen, Xiaoping; Liang, Xuanqiang; Wei, Xinghua

2018-01-01

Seed dormancy is an important agronomic trait affecting grain yield and quality because of pre-harvest germination and is influenced by both environmental and genetic factors. However, our knowledge of the factors controlling seed dormancy remains limited. To better reveal the molecular mechanism underlying this trait, a genome-wide association study was conducted in an indica-only population consisting of 453 accessions genotyped using 5,291 SNPs. Nine known and new significant SNPs were identified on eight chromosomes. These lead SNPs explained 34.9% of the phenotypic variation, and four of them were designed as dCAPS markers in the hope of accelerating molecular breeding. Moreover, a total of 212 candidate genes was predicted and eight candidate genes showed plant tissue-specific expression in expression profile data from different public bioinformatics databases. In particular, LOC_Os03g10110, which had a maize homolog involved in embryo development, was identified as a candidate regulator for further biological function investigations. Additionally, a polymorphism information content ratio method was used to screen improvement footprints and 27 selective sweeps were identified, most of which harbored domestication-related genes. Further studies suggested that three significant SNPs were adjacent to the candidate selection signals, supporting the accuracy of our genome-wide association study (GWAS) results. These findings show that genome-wide screening for selective sweeps can be used to identify new improvement-related DNA regions, although the phenotypes are unknown. This study enhances our knowledge of the genetic variation in seed dormancy, and the new dormancy-associated SNPs will provide real benefits in molecular breeding. PMID:29354150

Mapping and Genetic Structure Analysis of the Anthracnose Resistance Locus Co-1HY in the Common Bean (Phaseolus vulgaris L.).

PubMed

Chen, Mingli; Wu, Jing; Wang, Lanfen; Mantri, Nitin; Zhang, Xiaoyan; Zhu, Zhendong; Wang, Shumin

2017-01-01

Anthracnose is a destructive disease of the common bean (Phaseolus vulgaris L.). The Andean cultivar Hongyundou has been demonstrated to possess strong resistance to anthracnose race 81. To study the genetics of this resistance, the Hongyundou cultivar was crossed with a susceptible genotype Jingdou. Segregation of resistance for race 81 was assessed in the F2 population and F2:3 lines under controlled conditions. Results indicate that Hongyundou carries a single dominant gene for anthracnose resistance. An allele test by crossing Hongyundou with another resistant cultivar revealed that the resistance gene is in the Co-1 locus (therefore named Co-1HY). The physical distance between this locus and the two flanking markers was 46 kb, and this region included four candidate genes, namely, Phvul.001G243500, Phvul.001G243600, Phvul.001G243700 and Phvul.001G243800. These candidate genes encoded serine/threonine-protein kinases. Expression analysis of the four candidate genes in the resistant and susceptible cultivars under control condition and inoculated treatment revealed that all the four candidate genes are expressed at significantly higher levels in the resistant genotype than in susceptible genotype. Phvul.001G243600 and Phvul.001G243700 are expressed nearly 15-fold and 90-fold higher in the resistant genotype than in the susceptible parent before inoculation, respectively. Four candidate genes will provide useful information for further research into the resistance mechanism of anthracnose in common bean. The closely linked flanking markers identified here may be useful for transferring the resistance allele Co-1HY from Hongyundou to elite anthracnose susceptible common bean lines.

Mapping and Genetic Structure Analysis of the Anthracnose Resistance Locus Co-1HY in the Common Bean (Phaseolus vulgaris L.)

PubMed Central

Wang, Lanfen; Mantri, Nitin; Zhang, Xiaoyan; Zhu, Zhendong; Wang, Shumin

2017-01-01

Anthracnose is a destructive disease of the common bean (Phaseolus vulgaris L.). The Andean cultivar Hongyundou has been demonstrated to possess strong resistance to anthracnose race 81. To study the genetics of this resistance, the Hongyundou cultivar was crossed with a susceptible genotype Jingdou. Segregation of resistance for race 81 was assessed in the F2 population and F2:3 lines under controlled conditions. Results indicate that Hongyundou carries a single dominant gene for anthracnose resistance. An allele test by crossing Hongyundou with another resistant cultivar revealed that the resistance gene is in the Co-1 locus (therefore named Co-1HY). The physical distance between this locus and the two flanking markers was 46 kb, and this region included four candidate genes, namely, Phvul.001G243500, Phvul.001G243600, Phvul.001G243700 and Phvul.001G243800. These candidate genes encoded serine/threonine-protein kinases. Expression analysis of the four candidate genes in the resistant and susceptible cultivars under control condition and inoculated treatment revealed that all the four candidate genes are expressed at significantly higher levels in the resistant genotype than in susceptible genotype. Phvul.001G243600 and Phvul.001G243700 are expressed nearly 15-fold and 90-fold higher in the resistant genotype than in the susceptible parent before inoculation, respectively. Four candidate genes will provide useful information for further research into the resistance mechanism of anthracnose in common bean. The closely linked flanking markers identified here may be useful for transferring the resistance allele Co-1HY from Hongyundou to elite anthracnose susceptible common bean lines. PMID:28076395

Molecular insight into the association between cartilage regeneration and ear wound healing in genetic mouse models: targeting new genes in regeneration.

PubMed

Rai, Muhammad Farooq; Schmidt, Eric J; McAlinden, Audrey; Cheverud, James M; Sandell, Linda J

2013-11-06

Tissue regeneration is a complex trait with few genetic models available. Mouse strains LG/J and MRL are exceptional healers. Using recombinant inbred strains from a large (LG/J, healer) and small (SM/J, nonhealer) intercross, we have previously shown a positive genetic correlation between ear wound healing, knee cartilage regeneration, and protection from osteoarthritis. We hypothesize that a common set of genes operates in tissue healing and articular cartilage regeneration. Taking advantage of archived histological sections from recombinant inbred strains, we analyzed expression of candidate genes through branched-chain DNA technology directly from tissue lysates. We determined broad-sense heritability of candidates, Pearson correlation of candidates with healing phenotypes, and Ward minimum variance cluster analysis for strains. A bioinformatic assessment of allelic polymorphisms within and near candidate genes was also performed. The expression of several candidates was significantly heritable among strains. Although several genes correlated with both ear wound healing and cartilage healing at a marginal level, the expression of four genes representing DNA repair (Xrcc2, Pcna) and Wnt signaling (Axin2, Wnt16) pathways was significantly positively correlated with both phenotypes. Cluster analysis accurately classified healers and nonhealers for seven out of eight strains based on gene expression. Specific sequence differences between LG/J and SM/J were identified as potential causal polymorphisms. Our study suggests a common genetic basis between tissue healing and osteoarthritis susceptibility. Mapping genetic variations causing differences in diverse healing responses in multiple tissues may reveal generic healing processes in pursuit of new therapeutic targets designed to induce or enhance regeneration and, potentially, protection from osteoarthritis.

The Terpene Synthase Gene Family of Carrot (Daucus carota L.): Identification of QTLs and Candidate Genes Associated with Terpenoid Volatile Compounds

PubMed Central

Keilwagen, Jens; Lehnert, Heike; Berner, Thomas; Budahn, Holger; Nothnagel, Thomas; Ulrich, Detlef; Dunemann, Frank

2017-01-01

Terpenes are an important group of secondary metabolites in carrots influencing taste and flavor, and some of them might also play a role as bioactive substances with an impact on human physiology and health. Understanding the genetic and molecular basis of terpene synthases (TPS) involved in the biosynthesis of volatile terpenoids will provide insights for improving breeding strategies aimed at quality traits and for developing specific carrot chemotypes possibly useful for pharmaceutical applications. Hence, a combination of terpene metabolite profiling, genotyping-by-sequencing (GBS), and genome-wide association study (GWAS) was used in this work to get insights into the genetic control of terpene biosynthesis in carrots and to identify several TPS candidate genes that might be involved in the production of specific monoterpenes. In a panel of 85 carrot cultivars and accessions, metabolite profiling was used to identify 31 terpenoid volatile organic compounds (VOCs) in carrot leaves and roots, and a GBS approach was used to provide dense genome-wide marker coverage (>168,000 SNPs). Based on this data, a total of 30 quantitative trait loci (QTLs) was identified for 15 terpenoid volatiles. Most QTLs were detected for the monoterpene compounds ocimene, sabinene, β-pinene, borneol and bornyl acetate. We identified four genomic regions on three different carrot chromosomes by GWAS which are both associated with high significance (LOD ≥ 5.91) to distinct monoterpenes and to TPS candidate genes, which have been identified by homology-based gene prediction utilizing RNA-seq data. In total, 65 TPS candidate gene models in carrot were identified and assigned to known plant TPS subfamilies with the exception of TPS-d and TPS-h. TPS-b was identified as largest subfamily with 32 TPS candidate genes. PMID:29170675

3p22.1p21.31 microdeletion identifies CCK as Asperger syndrome candidate gene and shows the way for therapeutic strategies in chromosome imbalances.

PubMed

Iourov, Ivan Y; Vorsanova, Svetlana G; Voinova, Victoria Y; Yurov, Yuri B

2015-01-01

In contrast to other autism spectrum disorders, chromosome abnormalities are rare in Asperger syndrome (AS) or high-functioning autism. Consequently, AS was occasionally subjected to classical positional cloning. Here, we report on a case of AS associated with a deletion of the short arm of chromosome 3. Further in silico analysis has identified a candidate gene for AS and has suggested a therapeutic strategy for manifestations of the chromosome rearrangement. Using array comparative genomic hybridization, an interstitial deletion of 3p22.1p21.31 (~2.5 Mb in size) in a child with Asperger's syndrome, seborrheic dermatitis and chronic pancreatitis was detected. Original bioinformatic approach to the prioritization of candidate genes/processes identified CCK (cholecystokinin) as a candidate gene for AS. In addition to processes associated with deleted genes, bioinformatic analysis of CCK gene interactome indicated that zinc deficiency might be a pathogenic mechanism in this case. This suggestion was supported by plasma zinc concentration measurements. The increase of zinc intake produced a rise in zinc plasma concentration and the improvement in the patient's condition. Our study supported previous linkage findings and had suggested a new candidate gene in AS. Moreover, bioinformatic analysis identified the pathogenic mechanism, which was used to propose a therapeutic strategy for manifestations of the deletion. The relative success of this strategy allows speculating that therapeutic or dietary normalization of metabolic processes altered by a chromosome imbalance or genomic copy number variations may be a way for treating at least a small proportion of cases of these presumably incurable genetic conditions.

Replication and validation of genetic polymorphisms associated with survival after allogeneic blood or marrow transplant

PubMed Central

Karaesmen, Ezgi; Rizvi, Abbas A.; Preus, Leah M.; McCarthy, Philip L.; Pasquini, Marcelo C.; Onel, Kenan; Zhu, Xiaochun; Spellman, Stephen; Haiman, Christopher A.; Stram, Daniel O.; Pooler, Loreall; Sheng, Xin; Zhu, Qianqian; Yan, Li; Liu, Qian; Hu, Qiang; Webb, Amy; Brock, Guy; Clay-Gilmour, Alyssa I.; Battaglia, Sebastiano; Tritchler, David; Liu, Song; Hahn, Theresa

2017-01-01

Multiple candidate gene-association studies of non-HLA single-nucleotide polymorphisms (SNPs) and outcomes after blood or marrow transplant (BMT) have been conducted. We identified 70 publications reporting 45 SNPs in 36 genes significantly associated with disease-related mortality, progression-free survival, transplant-related mortality, and/or overall survival after BMT. Replication and validation of these SNP associations were performed using DISCOVeRY-BMT (Determining the Influence of Susceptibility COnveying Variants Related to one-Year mortality after BMT), a well-powered genome-wide association study consisting of 2 cohorts, totaling 2888 BMT recipients with acute myeloid leukemia, acute lymphoblastic leukemia, or myelodysplastic syndrome, and their HLA-matched unrelated donors, reported to the Center for International Blood and Marrow Transplant Research. Gene-based tests were used to assess the aggregate effect of SNPs on outcome. None of the previously reported significant SNPs replicated at P < .05 in DISCOVeRY-BMT. Validation analyses showed association with one previously reported donor SNP at P < .05 and survival; more associations would be anticipated by chance alone. No gene-based tests were significant at P < .05. Functional annotation with publicly available data shows these candidate SNPs most likely do not have biochemical function; only 13% of candidate SNPs correlate with gene expression or are predicted to impact transcription factor binding. Of these, half do not impact the candidate gene of interest; the other half correlate with expression of multiple genes. These findings emphasize the peril of pursing candidate approaches and the importance of adequately powered tests of unbiased genome-wide associations with BMT clinical outcomes given the ultimate goal of improving patient outcomes. PMID:28811306

RNA-Seq analysis and annotation of a draft blueberry genome assembly identifies candidate genes involved in fruit ripening, biosynthesis of bioactive compounds, and stage-specific alternative splicing.

PubMed

Gupta, Vikas; Estrada, April D; Blakley, Ivory; Reid, Rob; Patel, Ketan; Meyer, Mason D; Andersen, Stig Uggerhøj; Brown, Allan F; Lila, Mary Ann; Loraine, Ann E

2015-01-01

Blueberries are a rich source of antioxidants and other beneficial compounds that can protect against disease. Identifying genes involved in synthesis of bioactive compounds could enable the breeding of berry varieties with enhanced health benefits. Toward this end, we annotated a previously sequenced draft blueberry genome assembly using RNA-Seq data from five stages of berry fruit development and ripening. Genome-guided assembly of RNA-Seq read alignments combined with output from ab initio gene finders produced around 60,000 gene models, of which more than half were similar to proteins from other species, typically the grape Vitis vinifera. Comparison of gene models to the PlantCyc database of metabolic pathway enzymes identified candidate genes involved in synthesis of bioactive compounds, including bixin, an apocarotenoid with potential disease-fighting properties, and defense-related cyanogenic glycosides, which are toxic. Cyanogenic glycoside (CG) biosynthetic enzymes were highly expressed in green fruit, and a candidate CG detoxification enzyme was up-regulated during fruit ripening. Candidate genes for ethylene, anthocyanin, and 400 other biosynthetic pathways were also identified. Homology-based annotation using Blast2GO and InterPro assigned Gene Ontology terms to around 15,000 genes. RNA-Seq expression profiling showed that blueberry growth, maturation, and ripening involve dynamic gene expression changes, including coordinated up- and down-regulation of metabolic pathway enzymes and transcriptional regulators. Analysis of RNA-seq alignments identified developmentally regulated alternative splicing, promoter use, and 3' end formation. We report genome sequence, gene models, functional annotations, and RNA-Seq expression data that provide an important new resource enabling high throughput studies in blueberry.

Elasmobranch qPCR reference genes: a case study of hypoxia preconditioned epaulette sharks

PubMed Central

2010-01-01

Background Elasmobranch fishes are an ancient group of vertebrates which have high potential as model species for research into evolutionary physiology and genomics. However, no comparative studies have established suitable reference genes for quantitative PCR (qPCR) in elasmobranchs for any physiological conditions. Oxygen availability has been a major force shaping the physiological evolution of vertebrates, especially fishes. Here we examined the suitability of 9 reference candidates from various functional categories after a single hypoxic insult or after hypoxia preconditioning in epaulette shark (Hemiscyllium ocellatum). Results Epaulette sharks were caught and exposed to hypoxia. Tissues were collected from 10 controls, 10 individuals with single hypoxic insult and 10 individuals with hypoxia preconditioning (8 hypoxic insults, 12 hours apart). We produced sequence information for reference gene candidates and monitored mRNA expression levels in four tissues: cerebellum, heart, gill and eye. The stability of the genes was examined with analysis of variance, geNorm and NormFinder. The best ranking genes in our study were eukaryotic translation elongation factor 1 beta (eef1b), ubiquitin (ubq) and polymerase (RNA) II (DNA directed) polypeptide F (polr2f). The performance of the ribosomal protein L6 (rpl6) was tissue-dependent. Notably, in one tissue the analysis of variance indicated statistically significant differences between treatments for genes that were ranked as the most stable candidates by reference gene software. Conclusions Our results indicate that eef1b and ubq are generally the most suitable reference genes for the conditions and tissues in the present epaulette shark studies. These genes could also be potential reference gene candidates for other physiological studies examining stress in elasmobranchs. The results emphasise the importance of inter-group variation in reference gene evaluation. PMID:20416043

COL5A1: Genetic mapping and exclusion as candidate gene in families with nail-patella syndrome, tuberous sclerosis 1, hereditary hemorrhagic telangiectasia, and Ehlers-Danlos syndrome type II

DOE Office of Scientific and Technical Information (OSTI.GOV)

Greenspan, D.S.; Northrup, H.; Au, K.S.

1995-02-10

COL5A1, the gene for the {alpha}1 chain of type V collagen, has been considered a candidate gene for certain diseases based on chromosomal location and/or disease phenotype. We have employed 3{prime}-untranslated region RFLPs to exclude COL5A1 as a candidate gene in families with tuberous sclerosis 1, Ehlers-Danlos syndrome type H, and nail-patella syndrome. In addition, we describe a polymorphic simple sequence repeat (SSR) within a COL5A1 intron. This SSR is used to exclude COL5A1 as a candidate gene in hereditary hemorrhagic telangiectasia (Osler-Rendu-Weber disease) and to add COL5A1 to the existing map of {open_quotes}index{close_quotes} markers of chromosome 9 by evaluationmore » of the COL5A1 locus on the CEPH 40-family reference pedigree set. This genetic mapping places COL5A1 between markers D9S66 and D9S67. 14 refs., 1 fig., 2 tabs.« less

Haplotype diversity in 11 candidate genes across four populations.

PubMed

Beaty, T H; Fallin, M D; Hetmanski, J B; McIntosh, I; Chong, S S; Ingersoll, R; Sheng, X; Chakraborty, R; Scott, A F

2005-09-01

Analysis of haplotypes based on multiple single-nucleotide polymorphisms (SNP) is becoming common for both candidate gene and fine-mapping studies. Before embarking on studies of haplotypes from genetically distinct populations, however, it is important to consider variation both in linkage disequilibrium (LD) and in haplotype frequencies within and across populations, as both vary. Such diversity will influence the choice of "tagging" SNPs for candidate gene or whole-genome association studies because some markers will not be polymorphic in all samples and some haplotypes will be poorly represented or completely absent. Here we analyze 11 genes, originally chosen as candidate genes for oral clefts, where multiple markers were genotyped on individuals from four populations. Estimated haplotype frequencies, measures of pairwise LD, and genetic diversity were computed for 135 European-Americans, 57 Chinese-Singaporeans, 45 Malay-Singaporeans, and 46 Indian-Singaporeans. Patterns of pairwise LD were compared across these four populations and haplotype frequencies were used to assess genetic variation. Although these populations are fairly similar in allele frequencies and overall patterns of LD, both haplotype frequencies and genetic diversity varied significantly across populations. Such haplotype diversity has implications for designing studies of association involving samples from genetically distinct populations.

A Network Approach to Rare Disease Modeling

NASA Astrophysics Data System (ADS)

Ghiassian, Susan; Rabello, Sabrina; Sharma, Amitabh; Wiest, Olaf; Barabasi, Albert-Laszlo

2011-03-01

Network approaches have been widely used to better understand different areas of natural and social sciences. Network Science had a particularly great impact on the study of biological systems. In this project, using biological networks, candidate drugs as a potential treatment of rare diseases were identified. Developing new drugs for more than 2000 rare diseases (as defined by ORPHANET) is too expensive and beyond expectation. Disease proteins do not function in isolation but in cooperation with other interacting proteins. Research on FDA approved drugs have shown that most of the drugs do not target the disease protein but a protein which is 2 or 3 steps away from the disease protein in the Protein-Protein Interaction (PPI) network. We identified the already known drug targets in the disease gene's PPI subnetwork (up to the 3rd neighborhood) and among them those in the same sub cellular compartment and higher coexpression coefficient with the disease gene are expected to be stronger candidates. Out of 2177 rare diseases, 1092 were found not to have any drug target. Using the above method, we have found the strongest candidates among the rest in order to further experimental validations.

A search for imprinted quantitative trait loci (QTLs) for birth weight

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pandya, A.; Llewellyn, B.; Schieken, R.

1994-09-01

Previous studies have generally provided strong evidence that maternal effects are a much more important determinant of birth weight than the genes of the fetus. In the past, these findings have been interpreted as reflecting a genetically determined maternal constraint on fetal growth. However, the recognition that the expression of a gene can be influenced by its parental origin has provided an alternative explanation for apparent maternal effects. In the mouse, a growing number of imprinted genes have been identified which can profoundly influence birth weight or body size including IGF-1, IGF-2, and their respective receptor loci. To determine whethermore » any of the loci are QTLs for body size in man, we have used parental typing data to classify dizygotic twins according to their identity by descent (IBD) for polymorphic markers at or near the candidate loci. The contrast between the correlations of DZ pairs sharing both alleles IBD and no alleles IBD can provide evidence for a candidate gene effect while the contrast between twins sharing one maternal or one paternal allele IBD can provide evidence for any effect of imprinting that may exist at the locus. Finally, the inclusion of data on MZ twins in an overall analysis permits the resolution of the imprinting and marker gene effects from other sources of genetic and environmental variation. We have applied this model to birth weight data on 181 pairs of twins who were classified according to their allele sharing at the IGF-1 locus. In keeping with other observations, the data show no evidence that the IGF-1 locus is imprinted in man. Although our results are consistent with the possibility that this locus may account for 15-20% of the genetic variation, the apparent effect is not statistically significant. Partitioned twin analysis appears to be a useful method for detecting the effects of specific candidate gene on continuously distributed traits.« less

Pharmacogenetics of risperidone therapy in autism: association analysis of eight candidate genes with drug efficacy and adverse drug reactions.

PubMed

Correia, C T; Almeida, J P; Santos, P E; Sequeira, A F; Marques, C E; Miguel, T S; Abreu, R L; Oliveira, G G; Vicente, A M

2010-10-01

Little has been reported on the factors, genetic or other, that underlie the variability in individual response, particularly for autism. In this study we simultaneously explored the effects of multiple candidate genes on clinical improvement and occurrence of adverse drug reactions, in 45 autistic patients who received monotherapy with risperidone up to 1 year. Candidate genes involved in the pharmacokinetics (CYP2D6 and ABCB1) and pharmacodynamics (HTR2A, HTR2C, DRD2, DRD3, HTR6) of the drug, and the brain-derived neurotrophic factor (BDNF) gene, were analysed. Using the generalized estimating equation method these genes were tested for association with drug efficacy, assessed with the Autism Treatment Evaluation Checklist, and with safety and tolerability measures, such as prolactin levels, body mass index (BMI), waist circumference and neurological adverse effects, including extrapyramidal movements. Our results confirm that risperidone therapy was very effective in reducing some autism symptoms and caused few serious adverse effects. After adjusting for confounding factors, the HTR2A c.-1438G>A, DRD3 Ser9Gly, HTR2C c.995G>A and ABCB1 1236C>T polymorphisms were predictors for clinical improvement with risperidone therapy. The HTR2A c.-1438G>A, HTR2C c.68G>C (p.C33S), HTR6 c.7154-2542C>T and BDNF c.196G>A (p.V66M) polymorphisms influenced prolactin elevation. HTR2C c.68G>C and CYP2D6 polymorphisms were associated with risperidone-induced increase in BMI or waist circumference. We thus identified for the first time several genes implicated in risperidone efficacy and safety in autism patients. Although association results require replication, given the small sample size, the study makes a preliminary contribution to the personalized therapy of risperidone in autism.