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Sample records for genetic alterations prediction

  1. Genetic Alterations in Glioma

    International Nuclear Information System (INIS)

    Bralten, Linda B. C.; French, Pim J.

    2011-01-01

    Gliomas are the most common type of primary brain tumor and have a dismal prognosis. Understanding the genetic alterations that drive glioma formation and progression may help improve patient prognosis by identification of novel treatment targets. Recently, two major studies have performed in-depth mutation analysis of glioblastomas (the most common and aggressive subtype of glioma). This systematic approach revealed three major pathways that are affected in glioblastomas: The receptor tyrosine kinase signaling pathway, the TP53 pathway and the pRB pathway. Apart from frequent mutations in the IDH1/2 gene, much less is known about the causal genetic changes of grade II and III (anaplastic) gliomas. Exceptions include TP53 mutations and fusion genes involving the BRAF gene in astrocytic and pilocytic glioma subtypes, respectively. In this review, we provide an update on all common events involved in the initiation and/or progression across the different subtypes of glioma and provide future directions for research into the genetic changes

  2. Rare endocrine cancers have novel genetic alterations

    Science.gov (United States)

    A molecular characterization of adrenocortical carcinoma, a rare cancer of the adrenal cortex, analyzed 91 cases for alterations in the tumor genomes and identified several novel genetic mutations as likely mechanisms driving the disease as well as whole genome doubling as a probable driver of the disease.

  3. Genetic alterations in hepatocellular carcinoma: An update

    Science.gov (United States)

    Niu, Zhao-Shan; Niu, Xiao-Jun; Wang, Wen-Hong

    2016-01-01

    Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related deaths worldwide. Although recent advances in therapeutic approaches for treating HCC have improved the prognoses of patients with HCC, this cancer is still associated with a poor survival rate mainly due to late diagnosis. Therefore, a diagnosis must be made sufficiently early to perform curative and effective treatments. There is a need for a deeper understanding of the molecular mechanisms underlying the initiation and progression of HCC because these mechanisms are critical for making early diagnoses and developing novel therapeutic strategies. Over the past decade, much progress has been made in elucidating the molecular mechanisms underlying hepatocarcinogenesis. In particular, recent advances in next-generation sequencing technologies have revealed numerous genetic alterations, including recurrently mutated genes and dysregulated signaling pathways in HCC. A better understanding of the genetic alterations in HCC could contribute to identifying potential driver mutations and discovering novel therapeutic targets in the future. In this article, we summarize the current advances in research on the genetic alterations, including genomic instability, single-nucleotide polymorphisms, somatic mutations and deregulated signaling pathways, implicated in the initiation and progression of HCC. We also attempt to elucidate some of the genetic mechanisms that contribute to making early diagnoses of and developing molecularly targeted therapies for HCC. PMID:27895396

  4. [Colorectal cancer (CCR): genetic and molecular alterations].

    Science.gov (United States)

    Juárez-Vázquez, Clara Ibet; Rosales-Reynoso, Mónica Alejandra

    2014-01-01

    The aim of this review is to present a genetic and molecular overview of colorectal carcinogenesis (sporadic and hereditary origin) as a multistage process, where there are a number of molecular mechanisms associated with the development of colorectal cancer and genomic instability that allows the accumulation of mutations in proto-oncogenes and tumor suppressor genes, chromosomal instability, and methylation and microsatellite instability, and the involvement of altered expression of microRNAs' prognosis factors.

  5. Genetic alterations during radiation-induced carcinogenesis

    International Nuclear Information System (INIS)

    Kodama, Seiji

    1995-01-01

    This paper reviews radiation-induced genetic alterations and its carcinogenesis, focusing on the previous in vitro assay outcome. A colony formation assay using Syrian hamster fetal cells and focus formation assay using mouse C3H10T1/2 cells are currently available to find malignant transformation of cells. Such in vitro assays has proposed the hypothesis that radiation-induced carcinogenesis arises from at least two-stage processes; i.e., that an early step induced by irradiation plays an important role in promoting the potential to cause the subsequent mutation. A type of genetic instability induced by radiation results in a persistently elevated frequency of spontaneous mutations, so-called the phenomenon of delayed reproductive death. One possible mechanism by which genetic instability arises has been shown to be due to the development of abnormality in the gene group involved in the maintenance mechanism of genome stability. Another possibility has also been shown to stem from the loss of telomere (the extremities of a chromosome). The importance of search for radiation-induced genetic instability is emphasized in view of the elucidation of carcinogenesis. (N.K.)

  6. Parental Virtue and Prenatal Genetic Alteration Research.

    Science.gov (United States)

    Tonkens, Ryan

    2015-12-01

    Although the philosophical literature on the ethics of human prenatal genetic alteration (PGA) purports to inform us about how to act, it rarely explicitly recognizes the perspective of those who will be making the PGA decision in practice. Here I approach the ethics of PGA from a distinctly virtue-based perspective, taking seriously what it means to be a good parent making this decision for one's child. From this perspective, I generate a sound verdict on the moral standing of human PGA (research): given the current state of the art, good parents have compelling reason not to consent to PGA (research) for their child, especially as part of the first wave(s) of PGA research participants and especially for non-medically oriented purposes. This is because doing otherwise is inconsistent with a plausible and defensible understanding of virtuous parenting and parental virtues, founded on a genuine concern for promoting the overall flourishing of the eventual child. In essence, given the current and foreseeable state of the art, parents who allow prenatal genetic alteration of their children are less-than-virtuous parents to those children, even in cases where they have a right to do so and even if PGA turns out to be beneficial to the eventual child.

  7. Genetic alterations and epigenetic changes in hepatocarcinogenesis

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    Luz Stella Hoyos Giraldo

    2007-02-01

    Full Text Available

    Hepatocarcinogenesis as hepatocellular carcinoma (HCC is associated with background of chronic liver disease usually in association with cirrhosis, marked hepatic fibrosis, hepatitis B virus (HBV and/or hepatitis virus (HCV infection, chronic inflammation, Aflatoxin B1(AFB1 exposure, chronic alcoholism, metabolic disorder of the liver and necroinflamatory liver disease. Hepatocarcinogenesis involve two mechanisms, genetic alterations (with changes in the cell's DNA sequence and epigenetic changes (without changes in the cell's DNA sequence, but changes in the pattern of gene expression that can persist through one or more generations (somatic sense. Hepatocarcinogenesis is associated with activation of oncogenes and decreased expression of tumor suppressor genes (TSG; include those involved in cell cycle control, apoptosis, DNA repair, immortalization and angiogenesis. AFB1 is metabolized in the liver into a potent carcinogen, aflatoxin 8, 9-epoxide, which is detoxified by epoxide hydrolase (EPHX and glutathione S-transferase M1 (GSTM1.

    A failure of detoxification processes can allow to mutagenic metabolite to bind to DNA and inducing P53 mutation. Genetic polymorphism of EPHX and GSTM1 can make individuals more susceptible to AFB1. Epigenetic inactivation of GSTP1 by promoter hypermethylation plays a role in the development of HCC because, it leads that electrophilic metabolite increase DNA damage and mutations. HBV DNA integration into the host chromosomal DNA of hepatocytes has been detected in HBV-related HCC.

    DNA tumor viruses cause cancer mainly by interfering with cell cycle controls, and activating the cell's replication machinery by blocking the action of key TSG. HBx protein is a

  8. Genetic Alterations in Pesticide Exposed Bolivian Farmers

    DEFF Research Database (Denmark)

    Jørs, Erik; González, Ana Rosa; Ascarrunz, Maria Eugenia

    2007-01-01

    : Questionnaires were applied and blood tests taken from 81 volunteers from La Paz County, of whom 48 were pesticide exposed farmers and 33 non-exposed controls. Sixty males and 21 females participated with a mean age of 37.3 years (range 17-76). Data of exposure and possible genetic damage were collected...... and evaluated by well known statistical methods, controlling for relevant confounders. To measure genetic damage chromosomal aberrations and the comet assay analysis were performed. Results: Pesticide exposed farmers had a higher degree of genetic damage compared to the control group. The number of chromosomal......, probably related to exposure to pesticides. Due to the potentially negative long term health effects of genetic damage on reproduction and the development of cancer, preventive measures are recommended. Effective control with imports and sales, banning of the most toxic pesticides, education...

  9. Genetic alterations in syndromes with oral manifestations

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    Krishnamurthy Anuthama

    2013-01-01

    Full Text Available Ever since Gregor Johan Mendel proposed the law of inheritance, genetics has transcended the field of health and has entered all walks of life in its application. Thus, the gene is the pivoting factor for all happenings revolving around it. Knowledge of gene mapping in various diseases would be a valuable tool in prenatally diagnosing the condition and averting the future disability and stigma for the posterity. This article includes an array of genetically determined conditions in patients seen at our college out-patient department with complete manifestation, partial manifestation and array of manifestations not fitting into a particular syndrome.

  10. Genetic alterations in B-cell non-Hodgkin's lymphoma

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    Magić Zvonko

    2005-01-01

    BMT. Conclusion. Because it is quick and simple, PCR analysis of clonal IgH rearrangements is very useful when diagnostic assistance is required. This technique is also very efficient for tracking minimal residual disease in lymphomas and leukemia's and for monitoring clonal evolution in acute and chronic lymphoblastic leukemia's and lymphomas. The presence of other genetic alterations, which we detected, should serve as an additional prognostic or predictive factor in the patients with B-NHL.

  11. Distinct genetic alterations in colorectal cancer.

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    Hassan Ashktorab

    Full Text Available BACKGROUND: Colon cancer (CRC development often includes chromosomal instability (CIN leading to amplifications and deletions of large DNA segments. Epidemiological, clinical, and cytogenetic studies showed that there are considerable differences between CRC tumors from African Americans (AAs and Caucasian patients. In this study, we determined genomic copy number aberrations in sporadic CRC tumors from AAs, in order to investigate possible explanations for the observed disparities. METHODOLOGY/PRINCIPAL FINDINGS: We applied genome-wide array comparative genome hybridization (aCGH using a 105k chip to identify copy number aberrations in samples from 15 AAs. In addition, we did a population comparative analysis with aCGH data in Caucasians as well as with a widely publicized list of colon cancer genes (CAN genes. There was an average of 20 aberrations per patient with more amplifications than deletions. Analysis of DNA copy number of frequently altered chromosomes revealed that deletions occurred primarily in chromosomes 4, 8 and 18. Chromosomal duplications occurred in more than 50% of cases on chromosomes 7, 8, 13, 20 and X. The CIN profile showed some differences when compared to Caucasian alterations. CONCLUSIONS/SIGNIFICANCE: Chromosome X amplification in male patients and chromosomes 4, 8 and 18 deletions were prominent aberrations in AAs. Some CAN genes were altered at high frequencies in AAs with EXOC4, EPHB6, GNAS, MLL3 and TBX22 as the most frequently deleted genes and HAPLN1, ADAM29, SMAD2 and SMAD4 as the most frequently amplified genes. The observed CIN may play a distinctive role in CRC in AAs.

  12. Genetic Alterations in Intervertebral Disc Disease

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    Nikolay L. Martirosyan

    2016-11-01

    Full Text Available Background: Intervertebral disc degeneration (IVDD is considered a multifactorial disease. The last two decades of research strongly demonstrate that genetic factors contribute about 75% of the IVDD etiology. Recent total genome sequencing studies have shed light on the various single nucleotide polymorphisms (SNPs that are associated with IVDD.Aim: This review explores and presents updated information about the diversity of genetic factors in the inflammatory, degradative, homeostatic, and structural systems involved in the IVDD.Results: SNPs in the genes coding for structural proteins linked with IVDD or disc bulging include the Sp1 polymorphism of COL1A1, Trp3 polymorphism of COL9A3, several polymorphisms of COL11A1 and COL11A2, and a variable number tandem repeat polymorphism of ACAN. The rs4148941 SNP of CHST3 coding for an aggrecan sulfation enzyme is also associated with IVDD. The FokI, TaqI, and ApaI SNPs of the vitamin D receptor gene that is involved in chondrocyte functioning are also associated with IVDD. SNPs relevant to cytokine imbalance in IVDD include 889C/T of IL1a and 15T/A, as well as other SNPs (rs1800795, rs1800796, and rs1800797, of IL6, with effects limited to certain genders and populations. SNPs in collagenase genes include -1605G/D (guanine insertion/deletion of MMP1, -1306C/T of MMP2, -1562C/T and a 5-adenosine (5A variant (in the promotor region of MMP3, -1562C/T of MMP9, and -378T/C of MMP-14. SNPs in aggrecanase genes include 1877T/U of ADAMTS-4 and rs162509 of ADAMTS-5. Among the apoptosis-mediating genes, 1595T/C of the caspase 9 gene, 1525A/G and 1595T/C of the TRAIL gene, and 626C/G of the death receptor 4 gene (DR4 are SNPs associated with IVDD. Among the growth factors involved in disc homeostasis, the rs4871857 SNP of GDF5 was associated with IVDD. VEGF SNPs -2578C/A and -634G/C could foster neovascularization observed in IVDD.Conclusion: Improved understanding of the numerous genetic variants behind various

  13. The genetic alteration of p53 in esophageal cancer

    Energy Technology Data Exchange (ETDEWEB)

    Cho, Jae Il; Baik, Hee Jong; Kim, Chang Min; Kim, Mi Hee [Korea Cancer Center Hospital, Seoul (Korea, Republic of)

    1996-01-01

    Genetic alterations in the p53 gene have been detected in various human malignancies, and its alterations inactive the function of p53 as a tumor suppressor. Point mutation and gene deletion are the main mechanisms of p53 inactivation. To determine the incidence of genetic alteration of p53 and their clinical implications in Korean patients of esophageal cancer, we investigated p53 alterations in 26 esophageal cancer tissues paired with its normal tissue by Southern blot analysis, PCR-SSCP, and direct sequencing. Allelic loss of chromosome 17p occurred in 12 out of 21 informative cases(57%) by Southern blot analysis, and 16 cases showed mobility shift in PCR-SSCP, so overall incidence of p53 gene alterations was 77%(20/26). The mutations detected was randomly dispersed over exon4-8 and was frequently G-T transversion and C:T transitions. Three identical mutations were clustered at codon 213 suggested the same etiologic agents in this cases. The p53 gene alterations play a significant role in the development of esophageal cancers, however, no relationship between p53 mutation and clinical data was detected so far. 9 refs. (Author).

  14. Genetic alterations in head and neck squamous cell carcinomas

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    Nagai M.A.

    1999-01-01

    Full Text Available The genetic alterations observed in head and neck cancer are mainly due to oncogene activation (gain of function mutations and tumor suppressor gene inactivation (loss of function mutations, leading to deregulation of cell proliferation and death. These genetic alterations include gene amplification and overexpression of oncogenes such as myc, erbB-2, EGFR and cyclinD1 and mutations, deletions and hypermethylation leading to p16 and TP53 tumor suppressor gene inactivation. In addition, loss of heterozygosity in several chromosomal regions is frequently observed, suggesting that other tumor suppressor genes not yet identified could be involved in the tumorigenic process of head and neck cancers. The exact temporal sequence of the genetic alterations during head and neck squamous cell carcinoma (HNSCC development and progression has not yet been defined and their diagnostic or prognostic significance is controversial. Advances in the understanding of the molecular basis of head and neck cancer should help in the identification of new markers that could be used for the diagnosis, prognosis and treatment of the disease.

  15. The genetic alteration of retinoblastoma gene in esophageal cancer

    International Nuclear Information System (INIS)

    Cho, Jae Il; Shim, Yung Mok; Kim, Chang Min

    1994-12-01

    Retinoblastoma(RB) gene is the prototype of tumor suppressor gene and it's alteration have been frequently observed in a large number of human tumors. To investigate the role of RB in esophageal cancer, we studied 36 esophageal cancer tissues with Southern blot analysis to detect gross LOH and PCR-SSCP method to find minute LOH and mutation, if any. In the cases with abnormalities, the nucleotide sequence analysis was performed. Allelic loss of chromosome 13q14 occurred in 20 out of 32 informative cases (62.5%) by Southern analysis. Furthermore, PCR-LOH added three positive cases. Mobility shift by PCR-SSCP was observed in one case at exon 22, which showed 1 bp deletion in codon 771 of RB gene resulting in frame shift mutation. Besides, nine PCR-band alteration in tumor tissue compared with normal tissue were observed in exon 14 and 22, but mutation was not found on sequencing analysis suggesting the epigenetic alteration in tumor tissue. Analysis of the clinical data did not show any difference depending upon RB alteration. However, the total incidence of RB gene may play an important role in the development of esophageal cancer. The main genetic alteration of RB gene was deletion detected by Southern blot and one bp deletion leading to frame shift was also observed. 8 figs, 5 tabs. (Author)

  16. The genetic alteration of retinoblastoma gene in esophageal cancer

    Energy Technology Data Exchange (ETDEWEB)

    Cho, Jae Il; Shim, Yung Mok; Kim, Chang Min [Korea Cancer Center Hospital of Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

    1994-12-01

    Retinoblastoma(RB) gene is the prototype of tumor suppressor gene and it`s alteration have been frequently observed in a large number of human tumors. To investigate the role of RB in esophageal cancer, we studied 36 esophageal cancer tissues with Southern blot analysis to detect gross LOH and PCR-SSCP method to find minute LOH and mutation, if any. In the cases with abnormalities, the nucleotide sequence analysis was performed. Allelic loss of chromosome 13q14 occurred in 20 out of 32 informative cases (62.5%) by Southern analysis. Furthermore, PCR-LOH added three positive cases. Mobility shift by PCR-SSCP was observed in one case at exon 22, which showed 1 bp deletion in codon 771 of RB gene resulting in frame shift mutation. Besides, nine PCR-band alteration in tumor tissue compared with normal tissue were observed in exon 14 and 22, but mutation was not found on sequencing analysis suggesting the epigenetic alteration in tumor tissue. Analysis of the clinical data did not show any difference depending upon RB alteration. However, the total incidence of RB gene may play an important role in the development of esophageal cancer. The main genetic alteration of RB gene was deletion detected by Southern blot and one bp deletion leading to frame shift was also observed. 8 figs, 5 tabs. (Author).

  17. Genetic prediction of male pattern baldness.

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    Saskia P Hagenaars

    2017-02-01

    Full Text Available Male pattern baldness can have substantial psychosocial effects, and it has been phenotypically linked to adverse health outcomes such as prostate cancer and cardiovascular disease. We explored the genetic architecture of the trait using data from over 52,000 male participants of UK Biobank, aged 40-69 years. We identified over 250 independent genetic loci associated with severe hair loss (P<5x10-8. By splitting the cohort into a discovery sample of 40,000 and target sample of 12,000, we developed a prediction algorithm based entirely on common genetic variants that discriminated (AUC = 0.78, sensitivity = 0.74, specificity = 0.69, PPV = 59%, NPV = 82% those with no hair loss from those with severe hair loss. The results of this study might help identify those at greatest risk of hair loss, and also potential genetic targets for intervention.

  18. Genetic prediction of male pattern baldness.

    Science.gov (United States)

    Hagenaars, Saskia P; Hill, W David; Harris, Sarah E; Ritchie, Stuart J; Davies, Gail; Liewald, David C; Gale, Catharine R; Porteous, David J; Deary, Ian J; Marioni, Riccardo E

    2017-02-01

    Male pattern baldness can have substantial psychosocial effects, and it has been phenotypically linked to adverse health outcomes such as prostate cancer and cardiovascular disease. We explored the genetic architecture of the trait using data from over 52,000 male participants of UK Biobank, aged 40-69 years. We identified over 250 independent genetic loci associated with severe hair loss (P<5x10-8). By splitting the cohort into a discovery sample of 40,000 and target sample of 12,000, we developed a prediction algorithm based entirely on common genetic variants that discriminated (AUC = 0.78, sensitivity = 0.74, specificity = 0.69, PPV = 59%, NPV = 82%) those with no hair loss from those with severe hair loss. The results of this study might help identify those at greatest risk of hair loss, and also potential genetic targets for intervention.

  19. Genetic Alterations in Hungarian Patients with Papillary Thyroid Cancer.

    Science.gov (United States)

    Tobiás, Bálint; Halászlaki, Csaba; Balla, Bernadett; Kósa, János P; Árvai, Kristóf; Horváth, Péter; Takács, István; Nagy, Zsolt; Horváth, Evelin; Horányi, János; Járay, Balázs; Székely, Eszter; Székely, Tamás; Győri, Gabriella; Putz, Zsuzsanna; Dank, Magdolna; Valkusz, Zsuzsanna; Vasas, Béla; Iványi, Béla; Lakatos, Péter

    2016-01-01

    The incidence of thyroid cancers is increasing worldwide. Some somatic oncogene mutations (BRAF, NRAS, HRAS, KRAS) as well as gene translocations (RET/PTC, PAX8/PPAR-gamma) have been associated with the development of thyroid cancer. In our study, we analyzed these genetic alterations in 394 thyroid tissue samples (197 papillary carcinomas and 197 healthy). The somatic mutations and translocations were detected by Light Cycler melting method and Real-Time Polymerase Chain Reaction techniques, respectively. In tumorous samples, 86 BRAF (44.2%), 5 NRAS (3.1%), 2 HRAS (1.0%) and 1 KRAS (0.5%) mutations were found, as well as 9 RET/PTC1 (4.6%) and 1 RET/PTC3 (0.5%) translocations. No genetic alteration was seen in the non tumorous control thyroid tissues. No correlation was detected between the genetic variants and the pathological subtypes of papillary cancer as well as the severity of the disease. Our results are only partly concordant with the data found in the literature.

  20. Does genetic diversity predict health in humans?

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    Hanne C Lie

    2009-07-01

    Full Text Available Genetic diversity, especially at genes important for immune functioning within the Major Histocompatibility Complex (MHC, has been associated with fitness-related traits, including disease resistance, in many species. Recently, genetic diversity has been associated with mate preferences in humans. Here we asked whether these preferences are adaptive in terms of obtaining healthier mates. We investigated whether genetic diversity (heterozygosity and standardized mean d(2 at MHC and nonMHC microsatellite loci, predicted health in 153 individuals. Individuals with greater allelic diversity (d(2 at nonMHC loci and at one MHC locus, linked to HLA-DRB1, reported fewer symptoms over a four-month period than individuals with lower d(2. In contrast, there were no associations between MHC or nonMHC heterozygosity and health. NonMHC-d(2 has previously been found to predict male preferences for female faces. Thus, the current findings suggest that nonMHC diversity may play a role in both natural and sexual selection acting on human populations.

  1. Predicting mining activity with parallel genetic algorithms

    Science.gov (United States)

    Talaie, S.; Leigh, R.; Louis, S.J.; Raines, G.L.; Beyer, H.G.; O'Reilly, U.M.; Banzhaf, Arnold D.; Blum, W.; Bonabeau, C.; Cantu-Paz, E.W.; ,; ,

    2005-01-01

    We explore several different techniques in our quest to improve the overall model performance of a genetic algorithm calibrated probabilistic cellular automata. We use the Kappa statistic to measure correlation between ground truth data and data predicted by the model. Within the genetic algorithm, we introduce a new evaluation function sensitive to spatial correctness and we explore the idea of evolving different rule parameters for different subregions of the land. We reduce the time required to run a simulation from 6 hours to 10 minutes by parallelizing the code and employing a 10-node cluster. Our empirical results suggest that using the spatially sensitive evaluation function does indeed improve the performance of the model and our preliminary results also show that evolving different rule parameters for different regions tends to improve overall model performance. Copyright 2005 ACM.

  2. DNA Fingerprinting Techniques for the Analysis of Genetic and Epigenetic Alterations in Colorectal Cancer

    OpenAIRE

    Samuelsson, Johanna K.; Alonso, Sergio; Yamamoto, Fumiichiro; Perucho, Manuel

    2010-01-01

    Genetic somatic alterations are fundamental hallmarks of cancer. In addition to point and other small mutations targeting cancer genes, solid tumors often exhibit aneuploidy as well as multiple chromosomal rearrangements of large fragments of the genome. Whether somatic chromosomal alterations and aneuploidy are a driving force or a mere consequence of tumorigenesis remains controversial. Recently it became apparent that not only genetic but also epigenetic alterations play a major role in ca...

  3. A genetic code alteration is a phenotype diversity generator in the human pathogen Candida albicans.

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    Isabel Miranda

    Full Text Available BACKGROUND: The discovery of genetic code alterations and expansions in both prokaryotes and eukaryotes abolished the hypothesis of a frozen and universal genetic code and exposed unanticipated flexibility in codon and amino acid assignments. It is now clear that codon identity alterations involve sense and non-sense codons and can occur in organisms with complex genomes and proteomes. However, the biological functions, the molecular mechanisms of evolution and the diversity of genetic code alterations remain largely unknown. In various species of the genus Candida, the leucine CUG codon is decoded as serine by a unique serine tRNA that contains a leucine 5'-CAG-3'anticodon (tRNA(CAG(Ser. We are using this codon identity redefinition as a model system to elucidate the evolution of genetic code alterations. METHODOLOGY/PRINCIPAL FINDINGS: We have reconstructed the early stages of the Candida genetic code alteration by engineering tRNAs that partially reverted the identity of serine CUG codons back to their standard leucine meaning. Such genetic code manipulation had profound cellular consequences as it exposed important morphological variation, altered gene expression, re-arranged the karyotype, increased cell-cell adhesion and secretion of hydrolytic enzymes. CONCLUSION/SIGNIFICANCE: Our study provides the first experimental evidence for an important role of genetic code alterations as generators of phenotypic diversity of high selective potential and supports the hypothesis that they speed up evolution of new phenotypes.

  4. Predictability of Genetic Interactions from Functional Gene Modules

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    Jonathan H. Young

    2017-02-01

    Full Text Available Characterizing genetic interactions is crucial to understanding cellular and organismal response to gene-level perturbations. Such knowledge can inform the selection of candidate disease therapy targets, yet experimentally determining whether genes interact is technically nontrivial and time-consuming. High-fidelity prediction of different classes of genetic interactions in multiple organisms would substantially alleviate this experimental burden. Under the hypothesis that functionally related genes tend to share common genetic interaction partners, we evaluate a computational approach to predict genetic interactions in Homo sapiens, Drosophila melanogaster, and Saccharomyces cerevisiae. By leveraging knowledge of functional relationships between genes, we cross-validate predictions on known genetic interactions and observe high predictive power of multiple classes of genetic interactions in all three organisms. Additionally, our method suggests high-confidence candidate interaction pairs that can be directly experimentally tested. A web application is provided for users to query genes for predicted novel genetic interaction partners. Finally, by subsampling the known yeast genetic interaction network, we found that novel genetic interactions are predictable even when knowledge of currently known interactions is minimal.

  5. Genetic Alterations and Their Clinical Implications in High-Recurrence Risk Papillary Thyroid Cancer.

    Science.gov (United States)

    Lee, Min-Young; Ku, Bo Mi; Kim, Hae Su; Lee, Ji Yun; Lim, Sung Hee; Sun, Jong-Mu; Lee, Se-Hoon; Park, Keunchil; Oh, Young Lyun; Hong, Mineui; Jeong, Han-Sin; Son, Young-Ik; Baek, Chung-Hwan; Ahn, Myung-Ju

    2017-10-01

    Papillary thyroid carcinomas (PTCs) frequently involve genetic alterations. The objective of this study was to investigate genetic alterations and further explore the relationships between these genetic alterations and clinicopathological characteristics in a high-recurrence risk (node positive, N1) PTC group. Tumor tissue blocks were obtained from 240 surgically resected patients with histologically confirmed stage III/IV (pT3/4 or N1) PTCs. We screened gene fusions using NanoString's nCounter technology and mutational analysis was performed by direct DNA sequencing. Data describing the clinicopathological characteristics and clinical courses were retrospectively collected. Of the 240 PTC patients, 207 (86.3%) had at least one genetic alteration, including BRAF mutation in 190 patients (79.2%), PIK3CA mutation in 25 patients (10.4%), NTRK1/3 fusion in six patients (2.5%), and RET fusion in 24 patients (10.0%). Concomitant presence of more than two genetic alterations was seen in 36 patients (15%). PTCs harboring BRAF mutation were associated with RET wild-type expression (p=0.001). RET fusion genes have been found to occur with significantly higher frequency in N1b stage patients (p=0.003) or groups of patients aged 45 years or older (p=0.031); however, no significant correlation was found between other genetic alterations. There was no trend toward favorable recurrence-free survival or overall survival among patients lacking genetic alterations. In the selected high-recurrence risk PTC group, most patients had more than one genetic alteration. However, these known alterations could not entirely account for clinicopathological features of high-recurrence risk PTC.

  6. [Algorithm of toxigenic genetically altered Vibrio cholerae El Tor biovar strain identification].

    Science.gov (United States)

    Smirnova, N I; Agafonov, D A; Zadnova, S P; Cherkasov, A V; Kutyrev, V V

    2014-01-01

    Development of an algorithm of genetically altered Vibrio cholerae biovar El Tor strai identification that ensures determination of serogroup, serovar and biovar of the studied isolate based on pheno- and genotypic properties, detection of genetically altered cholera El Tor causative agents, their differentiation by epidemic potential as well as evaluation of variability of key pathogenicity genes. Complex analysis of 28 natural V. cholerae strains was carried out by using traditional microbiological methods, PCR and fragmentary sequencing. An algorithm of toxigenic genetically altered V. cholerae biovar El Tor strain identification was developed that includes 4 stages: determination of serogroup, serovar and biovar based on phenotypic properties, confirmation of serogroup and biovar based on molecular-genetic properties determination of strains as genetically altered, differentiation of genetically altered strains by their epidemic potential and detection of ctxB and tcpA key pathogenicity gene polymorphism. The algorithm is based on the use of traditional microbiological methods, PCR and sequencing of gene fragments. The use of the developed algorithm will increase the effectiveness of detection of genetically altered variants of the cholera El Tor causative agent, their differentiation by epidemic potential and will ensure establishment of polymorphism of genes that code key pathogenicity factors for determination of origins of the strains and possible routes of introduction of the infection.

  7. A novel nuclear genetic code alteration in yeasts and the evolution of codon reassignment in eukaryotes.

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    Mühlhausen, Stefanie; Findeisen, Peggy; Plessmann, Uwe; Urlaub, Henning; Kollmar, Martin

    2016-07-01

    The genetic code is the cellular translation table for the conversion of nucleotide sequences into amino acid sequences. Changes to the meaning of sense codons would introduce errors into almost every translated message and are expected to be highly detrimental. However, reassignment of single or multiple codons in mitochondria and nuclear genomes, although extremely rare, demonstrates that the code can evolve. Several models for the mechanism of alteration of nuclear genetic codes have been proposed (including "codon capture," "genome streamlining," and "ambiguous intermediate" theories), but with little resolution. Here, we report a novel sense codon reassignment in Pachysolen tannophilus, a yeast related to the Pichiaceae. By generating proteomics data and using tRNA sequence comparisons, we show that Pachysolen translates CUG codons as alanine and not as the more usual leucine. The Pachysolen tRNACAG is an anticodon-mutated tRNA(Ala) containing all major alanine tRNA recognition sites. The polyphyly of the CUG-decoding tRNAs in yeasts is best explained by a tRNA loss driven codon reassignment mechanism. Loss of the CUG-tRNA in the ancient yeast is followed by gradual decrease of respective codons and subsequent codon capture by tRNAs whose anticodon is not part of the aminoacyl-tRNA synthetase recognition region. Our hypothesis applies to all nuclear genetic code alterations and provides several testable predictions. We anticipate more codon reassignments to be uncovered in existing and upcoming genome projects. © 2016 Mühlhausen et al.; Published by Cold Spring Harbor Laboratory Press.

  8. Low Genetic Quality Alters Key Dimensions of the Mutational Spectrum.

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    Nathaniel P Sharp

    2016-03-01

    Full Text Available Mutations affect individual health, population persistence, adaptation, diversification, and genome evolution. There is evidence that the mutation rate varies among genotypes, but the causes of this variation are poorly understood. Here, we link differences in genetic quality with variation in spontaneous mutation in a Drosophila mutation accumulation experiment. We find that chromosomes maintained in low-quality genetic backgrounds experience a higher rate of indel mutation and a lower rate of gene conversion in a manner consistent with condition-based differences in the mechanisms used to repair DNA double strand breaks. These aspects of the mutational spectrum were also associated with body mass, suggesting that the effect of genetic quality on DNA repair was mediated by overall condition, and providing a mechanistic explanation for the differences in mutational fitness decline among these genotypes. The rate and spectrum of substitutions was unaffected by genetic quality, but we find variation in the probability of substitutions and indels with respect to several aspects of local sequence context, particularly GC content, with implications for models of molecular evolution and genome scans for signs of selection. Our finding that the chances of mutation depend on genetic context and overall condition has important implications for how sequences evolve, the risk of extinction, and human health.

  9. Predictive genetic tests: problems and pitfalls.

    Science.gov (United States)

    Davis, J G

    1997-12-29

    The role that genetic factors play in medicine has expanded, owing to such recent advances as those made by the Human Genome Project and the work that has spun off from it. The project is focusing particularly on localization and characterization of recognized human genetic disorders, which in turn increases awareness of the potential for improved treatment of these disorders. Technical advances in genetic testing in the absence of effective treatment has presented the health profession with major ethical challenges. The example of the identification of the BRCA1 and BRCA2 genes in families at high risk for breast and ovarian cancer is presented to illustrate the issues of the sensitivity of the method, the degree of susceptibility a positive result implies, the need for and availability of counseling and patient education, and confidentiality of the test results. A compelling need exists for adequate education about medical genetics to raise the "literacy" rate among health professionals.

  10. Somatic retrotransposition alters the genetic landscape of the human brain

    NARCIS (Netherlands)

    Baillie, J.K.; Barnett, M.W.; Upton, K.R.; Gerhardt, D.J.; Richmond, T.A.; De Sapio, F.; Brennan, P.; Rizzu, P.; Smith, S.; Fell, M.; Talbot, R.T.; Gustincich, S.; Freeman, T.C.; Mattick, J.S.; Hume, D.A.; Heutink, P.; Carninci, P.; Jeddeloh, J.A.; Faulkner, G.J.

    2011-01-01

    Retrotransposons are mobile genetic elements that use a germline 'copy-and-paste' mechanism to spread throughout metazoan genomes1. At least 50 per cent of the human genome is derived from retrotransposons, with three active families (L1, Alu and SVA) associated with insertional mutagenesis and

  11. How much do genetic covariances alter the rate of adaptation?

    Science.gov (United States)

    Agrawal, Aneil F; Stinchcombe, John R

    2009-03-22

    Genetically correlated traits do not evolve independently, and the covariances between traits affect the rate at which a population adapts to a specified selection regime. To measure the impact of genetic covariances on the rate of adaptation, we compare the rate fitness increases given the observed G matrix to the expected rate if all the covariances in the G matrix are set to zero. Using data from the literature, we estimate the effect of genetic covariances in real populations. We find no net tendency for covariances to constrain the rate of adaptation, though the quality and heterogeneity of the data limit the certainty of this result. There are some examples in which covariances strongly constrain the rate of adaptation but these are balanced by counter examples in which covariances facilitate the rate of adaptation; in many cases, covariances have little or no effect. We also discuss how our metric can be used to identify traits or suites of traits whose genetic covariances to other traits have a particularly large impact on the rate of adaptation.

  12. Potential genetic polymorphisms predicting polycystic ovary syndrome

    Directory of Open Access Journals (Sweden)

    Yao Chen

    2018-05-01

    Full Text Available Polycystic ovary syndrome (PCOS is a heterogenous endocrine disorder with typical symptoms of oligomenorrhoea, hyperandrogenism, hirsutism, obesity, insulin resistance and increased risk of type 2 diabetes mellitus. Extensive evidence indicates that PCOS is a genetic disease and numerous biochemical pathways have been linked with its pathogenesis. A number of genes from these pathways have been investigated, which include those involved with steroid hormone biosynthesis and metabolism, action of gonadotropin and gonadal hormones, folliculogenesis, obesity and energy regulation, insulin secretion and action and many others. In this review, we summarize the historical and recent findings in genetic polymorphisms of PCOS from the relevant publications and outline some genetic polymorphisms that are potentially associated with the risk of PCOS. This information could uncover candidate genes associating with PCOS, which will be valuable for the development of novel diagnostic and treatment platforms for PCOS patients.

  13. Critical roles for a genetic code alteration in the evolution of the genus Candida.

    Science.gov (United States)

    Silva, Raquel M; Paredes, João A; Moura, Gabriela R; Manadas, Bruno; Lima-Costa, Tatiana; Rocha, Rita; Miranda, Isabel; Gomes, Ana C; Koerkamp, Marian J G; Perrot, Michel; Holstege, Frank C P; Boucherie, Hélian; Santos, Manuel A S

    2007-10-31

    During the last 30 years, several alterations to the standard genetic code have been discovered in various bacterial and eukaryotic species. Sense and nonsense codons have been reassigned or reprogrammed to expand the genetic code to selenocysteine and pyrrolysine. These discoveries highlight unexpected flexibility in the genetic code, but do not elucidate how the organisms survived the proteome chaos generated by codon identity redefinition. In order to shed new light on this question, we have reconstructed a Candida genetic code alteration in Saccharomyces cerevisiae and used a combination of DNA microarrays, proteomics and genetics approaches to evaluate its impact on gene expression, adaptation and sexual reproduction. This genetic manipulation blocked mating, locked yeast in a diploid state, remodelled gene expression and created stress cross-protection that generated adaptive advantages under environmental challenging conditions. This study highlights unanticipated roles for codon identity redefinition during the evolution of the genus Candida, and strongly suggests that genetic code alterations create genetic barriers that speed up speciation.

  14. Implications of Genetic and Epigenetic Alterations of CDKN2A (p16INK4a in Cancer

    Directory of Open Access Journals (Sweden)

    Ran Zhao

    2016-06-01

    Full Text Available Aberrant gene silencing is highly associated with altered cell cycle regulation during carcinogenesis. In particular, silencing of the CDKN2A tumor suppressor gene, which encodes the p16INK4a protein, has a causal link with several different types of cancers. The p16INK4a protein plays an executional role in cell cycle and senescence through the regulation of the cyclin-dependent kinase (CDK 4/6 and cyclin D complexes. Several genetic and epigenetic aberrations of CDKN2A lead to enhanced tumorigenesis and metastasis with recurrence of cancer and poor prognosis. In these cases, the restoration of genetic and epigenetic reactivation of CDKN2A is a practical approach for the prevention and therapy of cancer. This review highlights the genetic status of CDKN2A as a prognostic and predictive biomarker in various cancers.

  15. Genetic alterations affecting cholesterol metabolism and human fertility.

    Science.gov (United States)

    DeAngelis, Anthony M; Roy-O'Reilly, Meaghan; Rodriguez, Annabelle

    2014-11-01

    Single nucleotide polymorphisms (SNPs) represent genetic variations among individuals in a population. In medicine, these small variations in the DNA sequence may significantly impact an individual's response to certain drugs or influence the risk of developing certain diseases. In the field of reproductive medicine, a significant amount of research has been devoted to identifying polymorphisms which may impact steroidogenesis and fertility. This review discusses current understanding of the effects of genetic variations in cholesterol metabolic pathways on human fertility that bridge novel linkages between cholesterol metabolism and reproductive health. For example, the role of the low-density lipoprotein receptor (LDLR) in cellular metabolism and human reproduction has been well studied, whereas there is now an emerging body of research on the role of the high-density lipoprotein (HDL) receptor scavenger receptor class B type I (SR-BI) in human lipid metabolism and female reproduction. Identifying and understanding how polymorphisms in the SCARB1 gene or other genes related to lipid metabolism impact human physiology is essential and will play a major role in the development of personalized medicine for improved diagnosis and treatment of infertility. © 2014 by the Society for the Study of Reproduction, Inc.

  16. Genetic Alterations in Gastric Cancer Associated with Helicobacter pylori Infection

    Directory of Open Access Journals (Sweden)

    Gonzalo Castillo-Rojas

    2017-05-01

    Full Text Available Gastric cancer is a world health problem and depicts the fourth leading mortality cause from malignancy in Mexico. Causation of gastric cancer is not only due to the combined effects of environmental factors and genetic variants. Recent molecular studies have transgressed a number of genes involved in gastric carcinogenesis. The aim of this review is to understand the recent basics of gene expression in the development of the process of gastric carcinogenesis. Genetic variants, polymorphisms, desoxyribonucleic acid methylation, and genes involved in mediating inflammation have been associated with the development of gastric carcinogenesis. Recently, these genes (interleukin 10, Il-17, mucin 1, β-catenin, CDX1, SMAD4, SERPINE1, hypoxia-inducible factor 1 subunit alpha, GSK3β, CDH17, matrix metalloproteinase 7, RUNX3, RASSF1A, TFF1, HAI-2, and COX-2 have been studied in association with oncogenic activation or inactivation of tumor suppressor genes. All these mechanisms have been investigated to elucidate the process of gastric carcinogenesis, as well as their potential use as biomarkers and/or molecular targets to treatment of disease.

  17. Analysis of Genetic Diversity of Two Mangrove Species with Morphological Alterations in a Natural Environment

    Directory of Open Access Journals (Sweden)

    Catarina Fonseca Lira-Medeiros

    2015-04-01

    Full Text Available Mangrove is an ecosystem subjected to tide, salinity and nutrient variations. These conditions are stressful to most plants, except to mangrove plants that are well-adapted. However, many mangrove areas have extremely stressful conditions, such as salt marshes, and the plants nearby usually present morphological alterations. In Sepetiba Bay, two species of mangrove plants, Avicennia schaueriana and Laguncularia racemosa, have poor development near a salt marsh (SM compared to plants at the riverside (RS, which is considered a favorable habitat in mangroves. The level of genetic diversity and its possible correlation with the morphological divergence of SM and RS plants of both species were assessed by AFLP molecular markers. We found moderate genetic differentiation between A. schaueriana plants from SM and RS areas and depleted genetic diversity on SM plants. On the other hand, Laguncularia racemosa plants had no genetic differentiation between areas. It is possible that a limited gene flow among the studied areas might be acting more intensely on A. schaueriana plants, resulting in the observed genetic differentiation. The populations of Laguncularia racemosa appear to be well connected, as genetic differentiation was not significant between the SM and RS populations. Gene flow and genetic drift are acting on neutral genetic diversity of these two mangrove species in the studied areas, and the observed genetic differentiation of A. schaueriana plants might be correlated with its morphological variation. For L. racemosa, morphological alterations could be related to epigenetic phenomena or adaptive loci polymorphism that should be further investigated.

  18. A Molecular Genetic Basis Explaining Altered Bacterial Behavior in Space.

    Directory of Open Access Journals (Sweden)

    Luis Zea

    Full Text Available Bacteria behave differently in space, as indicated by reports of reduced lag phase, higher final cell counts, enhanced biofilm formation, increased virulence, and reduced susceptibility to antibiotics. These phenomena are theorized, at least in part, to result from reduced mass transport in the local extracellular environment, where movement of molecules consumed and excreted by the cell is limited to diffusion in the absence of gravity-dependent convection. However, to date neither empirical nor computational approaches have been able to provide sufficient evidence to confirm this explanation. Molecular genetic analysis findings, conducted as part of a recent spaceflight investigation, support the proposed model. This investigation indicated an overexpression of genes associated with starvation, the search for alternative energy sources, increased metabolism, enhanced acetate production, and other systematic responses to acidity-all of which can be associated with reduced extracellular mass transport.

  19. A Molecular Genetic Basis Explaining Altered Bacterial Behavior in Space

    Science.gov (United States)

    Prasad, Nripesh; Levy, Shawn E.; Stodieck, Louis; Jones, Angela; Shrestha, Shristi; Klaus, David

    2016-01-01

    Bacteria behave differently in space, as indicated by reports of reduced lag phase, higher final cell counts, enhanced biofilm formation, increased virulence, and reduced susceptibility to antibiotics. These phenomena are theorized, at least in part, to result from reduced mass transport in the local extracellular environment, where movement of molecules consumed and excreted by the cell is limited to diffusion in the absence of gravity-dependent convection. However, to date neither empirical nor computational approaches have been able to provide sufficient evidence to confirm this explanation. Molecular genetic analysis findings, conducted as part of a recent spaceflight investigation, support the proposed model. This investigation indicated an overexpression of genes associated with starvation, the search for alternative energy sources, increased metabolism, enhanced acetate production, and other systematic responses to acidity—all of which can be associated with reduced extracellular mass transport. PMID:27806055

  20. Human diseases with genetically altered DNA repair processes

    International Nuclear Information System (INIS)

    Cleaver, J.E.; Bootsma, D.; Friedberg, E.

    1975-01-01

    DNA repair of single-strand breaks (produced by ionizing radiation) and of base damage (produced by ultraviolet (uv) light) are two repair mechanisms that most mammalian cells possess. Genetic defects in these repair mechanisms are exemplified by cells from the human premature-aging disease, progeria, which fail to rejoin single-strand breaks, and the skin disease, xeroderma pigmentosum (XP), which exhibits high actinic carcinogenesis and involves failure to repair base damage. In terms of the response of XP cells, many chemical carcinogens can be classified as either x-ray-like (i.e., they cause damage that XP cells can repair) or uv-like (i.e., they cause damage that XP cells cannot repair). The first group contains some of the more strongly carcinogenic chemicals (e.g., alkylating agents). XP occurs in at least two clinical forms, and somatic cell hybridization indicates at least three complementation groups. In order to identify cell lines from various different laboratories unambiguously, a modified nomenclature of XP lines is proposed. (U.S.)

  1. Human diseases with genetically altered DNA repair processes

    International Nuclear Information System (INIS)

    Cleaver, J.E.; Bootsma, D.; Friedberg, E.

    1975-01-01

    DNA repair of single-strand breaks (produced by ionizing radiation) and of base damage (produced by ultraviolet (UV) light) are two repair mechanisms that most mammalian cells possess. Genetic defects in these repair mechanisms are exemplified by cells from the human premature-aging disease, progeria, which fail to rejoin single-strand breaks, and the skin disease, xeroderma pigmentosum (XP), which exhibits high actinic carcinogenesis and involves failure to repair base damage. In terms of the response of XP cells, many chemical carcinogens can be classified as either X-ray-like (i.e., they cause damage that XP cells can repair) or UV-like (i.e., they cause damage that XP cells cannot repair). The first group contains some of the more strongly carcinogenic chemicals (e.g., alkylating agents). XP occurs in at least two clinical forms, and somatic cell hybridization indicates at least three complementation groups. In order to identify cell lines from various different laboratories unambiguously, a modified nomenclature of XP lines is proposed

  2. Radiation as agents of somatic and genetic alterations

    International Nuclear Information System (INIS)

    de Eston, V.R.

    1975-01-01

    According to the report on ''The Effects on Population of Exposure to Low Levels of Ionizing Radiation,'' whether we regard a risk as acceptable or not depends on how avoidable it is, and, if not avoidable, how it compares with the risks of alternative options and those usually accepted by society. Regarding the use of ionizing radiation: No exposure should be permitted without the expectation of a commensurable benefit. The public must be protected from radiation, but not to the extent that the degree of protection provided results in the substitution of a worse hazard than that of the radiation avoided. Medical radiation exposure can and should be reduced considerably by limiting its use to clinically indicated procedures, utilizing efficient exposure techniques and optimal operation of radiation equipment. Consideration should be given to the following: (a) Restriction of the use of radiation for public health purposes, unless there is reasonable probability of significant detection of disease. (b) Inspection and licensing of radiation and ancillary equipment. (c) Appropriate training and certification of involved personnel. (d) Gonad shielding, especially shielding of the testis, is strongly recommended as a simple and highly efficient way to reduce the genetic significant dose. In a poignant phrase, Morgan has stated ''Radiation doesn't have to be feared, but should be respected.''

  3. Genetic and epigenetic alterations induced by different levels of rye genome integration in wheat recipient.

    Science.gov (United States)

    Zheng, X L; Zhou, J P; Zang, L L; Tang, A T; Liu, D Q; Deng, K J; Zhang, Y

    2016-06-17

    The narrow genetic variation present in common wheat (Triticum aestivum) varieties has greatly restricted the improvement of crop yield in modern breeding systems. Alien addition lines have proven to be an effective means to broaden the genetic diversity of common wheat. Wheat-rye addition lines, which are the direct bridge materials for wheat improvement, have been wildly used to produce new wheat cultivars carrying alien rye germplasm. In this study, we investigated the genetic and epigenetic alterations in two sets of wheat-rye disomic addition lines (1R-7R) and the corresponding triticales. We used expressed sequence tag-simple sequence repeat, amplified fragment length polymorphism, and methylation-sensitive amplification polymorphism analyses to analyze the effects of the introduction of alien chromosomes (either the entire genome or sub-genome) to wheat genetic background. We found obvious and diversiform variations in the genomic primary structure, as well as alterations in the extent and pattern of the genomic DNA methylation of the recipient. Meanwhile, these results also showed that introduction of different rye chromosomes could induce different genetic and epigenetic alterations in its recipient, and the genetic background of the parents is an important factor for genomic and epigenetic variation induced by alien chromosome addition.

  4. Real coded genetic algorithm for fuzzy time series prediction

    Science.gov (United States)

    Jain, Shilpa; Bisht, Dinesh C. S.; Singh, Phool; Mathpal, Prakash C.

    2017-10-01

    Genetic Algorithm (GA) forms a subset of evolutionary computing, rapidly growing area of Artificial Intelligence (A.I.). Some variants of GA are binary GA, real GA, messy GA, micro GA, saw tooth GA, differential evolution GA. This research article presents a real coded GA for predicting enrollments of University of Alabama. Data of Alabama University is a fuzzy time series. Here, fuzzy logic is used to predict enrollments of Alabama University and genetic algorithm optimizes fuzzy intervals. Results are compared to other eminent author works and found satisfactory, and states that real coded GA are fast and accurate.

  5. Genetic alterations during the progression of squamous cell carcinomas of the uterine cervix

    NARCIS (Netherlands)

    Kersemaekers, A. M.; van de Vijver, M. J.; Kenter, G. G.; Fleuren, G. J.

    1999-01-01

    Most cervical carcinomas appear to arise from cervical intraepithelial neoplasia (CIN) lesions. In addition to infection with high-risk human papilloma viruses, which is indicative of an increased risk of progression, alterations of oncogenes and tumor suppressor genes play a role. Genetic studies

  6. The wild life at Chernobyl. Analysis of a prosperous but genetically altered fauna

    International Nuclear Information System (INIS)

    Chesser, R.; Baker, R.

    1996-01-01

    The ecological study of zones contaminated by Chernobyl accident reveals that the wild life abounds, because of inhabitants absence, evacuated. On the other hand, significant genetical alterations are observed, whom functional consequences, low visible, stay, at term, unknown. This kind of studies illustrates the development of a new discipline, the evolving toxicology

  7. Using Genetic Distance to Infer the Accuracy of Genomic Prediction.

    Directory of Open Access Journals (Sweden)

    Marco Scutari

    2016-09-01

    Full Text Available The prediction of phenotypic traits using high-density genomic data has many applications such as the selection of plants and animals of commercial interest; and it is expected to play an increasing role in medical diagnostics. Statistical models used for this task are usually tested using cross-validation, which implicitly assumes that new individuals (whose phenotypes we would like to predict originate from the same population the genomic prediction model is trained on. In this paper we propose an approach based on clustering and resampling to investigate the effect of increasing genetic distance between training and target populations when predicting quantitative traits. This is important for plant and animal genetics, where genomic selection programs rely on the precision of predictions in future rounds of breeding. Therefore, estimating how quickly predictive accuracy decays is important in deciding which training population to use and how often the model has to be recalibrated. We find that the correlation between true and predicted values decays approximately linearly with respect to either FST or mean kinship between the training and the target populations. We illustrate this relationship using simulations and a collection of data sets from mice, wheat and human genetics.

  8. DNA fingerprinting techniques for the analysis of genetic and epigenetic alterations in colorectal cancer.

    Science.gov (United States)

    Samuelsson, Johanna K; Alonso, Sergio; Yamamoto, Fumiichiro; Perucho, Manuel

    2010-11-10

    Genetic somatic alterations are fundamental hallmarks of cancer. In addition to point and other small mutations targeting cancer genes, solid tumors often exhibit aneuploidy as well as multiple chromosomal rearrangements of large fragments of the genome. Whether somatic chromosomal alterations and aneuploidy are a driving force or a mere consequence of tumorigenesis remains controversial. Recently it became apparent that not only genetic but also epigenetic alterations play a major role in carcinogenesis. Epigenetic regulation mechanisms underlie the maintenance of cell identity crucial for development and differentiation. These epigenetic regulatory mechanisms have been found substantially altered during cancer development and progression. In this review, we discuss approaches designed to analyze genetic and epigenetic alterations in colorectal cancer, especially DNA fingerprinting approaches to detect changes in DNA copy number and methylation. DNA fingerprinting techniques, despite their modest throughput, played a pivotal role in significant discoveries in the molecular basis of colorectal cancer. The aim of this review is to revisit the fingerprinting technologies employed and the oncogenic processes that they unveiled. 2010 Elsevier B.V. All rights reserved.

  9. Geometric Semantic Genetic Programming Algorithm and Slump Prediction

    OpenAIRE

    Xu, Juncai; Shen, Zhenzhong; Ren, Qingwen; Xie, Xin; Yang, Zhengyu

    2017-01-01

    Research on the performance of recycled concrete as building material in the current world is an important subject. Given the complex composition of recycled concrete, conventional methods for forecasting slump scarcely obtain satisfactory results. Based on theory of nonlinear prediction method, we propose a recycled concrete slump prediction model based on geometric semantic genetic programming (GSGP) and combined it with recycled concrete features. Tests show that the model can accurately p...

  10. Intrinsic Noise Profoundly Alters the Dynamics and Steady State of Morphogen-Controlled Bistable Genetic Switches.

    Directory of Open Access Journals (Sweden)

    Ruben Perez-Carrasco

    2016-10-01

    Full Text Available During tissue development, patterns of gene expression determine the spatial arrangement of cell types. In many cases, gradients of secreted signalling molecules-morphogens-guide this process by controlling downstream transcriptional networks. A mechanism commonly used in these networks to convert the continuous information provided by the gradient into discrete transitions between adjacent cell types is the genetic toggle switch, composed of cross-repressing transcriptional determinants. Previous analyses have emphasised the steady state output of these mechanisms. Here, we explore the dynamics of the toggle switch and use exact numerical simulations of the kinetic reactions, the corresponding Chemical Langevin Equation, and Minimum Action Path theory to establish a framework for studying the effect of gene expression noise on patterning time and boundary position. This provides insight into the time scale, gene expression trajectories and directionality of stochastic switching events between cell states. Taking gene expression noise into account predicts that the final boundary position of a morphogen-induced toggle switch, although robust to changes in the details of the noise, is distinct from that of the deterministic system. Moreover, the dramatic increase in patterning time close to the boundary predicted from the deterministic case is substantially reduced. The resulting stochastic switching introduces differences in patterning time along the morphogen gradient that result in a patterning wave propagating away from the morphogen source with a velocity determined by the intrinsic noise. The wave sharpens and slows as it advances and may never reach steady state in a biologically relevant time. This could explain experimentally observed dynamics of pattern formation. Together the analysis reveals the importance of dynamical transients for understanding morphogen-driven transcriptional networks and indicates that gene expression noise can

  11. Intrinsic Noise Profoundly Alters the Dynamics and Steady State of Morphogen-Controlled Bistable Genetic Switches

    Science.gov (United States)

    Page, Karen M.

    2016-01-01

    During tissue development, patterns of gene expression determine the spatial arrangement of cell types. In many cases, gradients of secreted signalling molecules—morphogens—guide this process by controlling downstream transcriptional networks. A mechanism commonly used in these networks to convert the continuous information provided by the gradient into discrete transitions between adjacent cell types is the genetic toggle switch, composed of cross-repressing transcriptional determinants. Previous analyses have emphasised the steady state output of these mechanisms. Here, we explore the dynamics of the toggle switch and use exact numerical simulations of the kinetic reactions, the corresponding Chemical Langevin Equation, and Minimum Action Path theory to establish a framework for studying the effect of gene expression noise on patterning time and boundary position. This provides insight into the time scale, gene expression trajectories and directionality of stochastic switching events between cell states. Taking gene expression noise into account predicts that the final boundary position of a morphogen-induced toggle switch, although robust to changes in the details of the noise, is distinct from that of the deterministic system. Moreover, the dramatic increase in patterning time close to the boundary predicted from the deterministic case is substantially reduced. The resulting stochastic switching introduces differences in patterning time along the morphogen gradient that result in a patterning wave propagating away from the morphogen source with a velocity determined by the intrinsic noise. The wave sharpens and slows as it advances and may never reach steady state in a biologically relevant time. This could explain experimentally observed dynamics of pattern formation. Together the analysis reveals the importance of dynamical transients for understanding morphogen-driven transcriptional networks and indicates that gene expression noise can qualitatively

  12. Use of multiple genetic markers in prediction of breeding values.

    NARCIS (Netherlands)

    Arendonk, van J.A.M.; Tier, B.; Kinghorn, B.P.

    1994-01-01

    Genotypes at a marker locus give information on transmission of genes from parents to offspring and that information can be used in predicting the individuals' additive genetic value at a linked quantitative trait locus (MQTL). In this paper a recursive method is presented to build the gametic

  13. Genetic selection for coping style predicts stressor susceptibility

    NARCIS (Netherlands)

    Veenema, AH; Meijer, OC; de Kloet, ER; Koolhaas, JM

    Genetically selected aggressive (SAL) and nonaggressive (LAL) male wild house-mice which show distinctly different coping styles, also display a differential regulation of the hypothalamic-pituitary-adrenal axis after exposure to an acute stressor. To test the hypothesis that coping style predicts

  14. Ethical issues in predictive genetic testing: a public health perspective

    Science.gov (United States)

    Fulda, K G; Lykens, K

    2006-01-01

    As a result of the increase in genetic testing and the fear of discrimination by insurance companies, employers, and society as a result of genetic testing, the disciplines of ethics, public health, and genetics have converged. Whether relatives of someone with a positive predictive genetic test should be notified of the results and risks is a matter urgently in need of debate. Such a debate must encompass the moral and ethical obligations of the diagnosing physician and the patient. The decision to inform or not will vary depending on what moral theory is used. Utilising the utilitarian and libertarian theories produces different outcomes. The principles of justice and non‐maleficence will also play an important role in the decision. PMID:16507657

  15. Ethical issues in predictive genetic testing: a public health perspective.

    Science.gov (United States)

    Fulda, K G; Lykens, K

    2006-03-01

    As a result of the increase in genetic testing and the fear of discrimination by insurance companies, employers, and society as a result of genetic testing, the disciplines of ethics, public health, and genetics have converged. Whether relatives of someone with a positive predictive genetic test should be notified of the results and risks is a matter urgently in need of debate. Such a debate must encompass the moral and ethical obligations of the diagnosing physician and the patient. The decision to inform or not will vary depending on what moral theory is used. Utilising the utilitarian and libertarian theories produces different outcomes. The principles of justice and non-maleficence will also play an important role in the decision.

  16. Altered expression of MGMT in high-grade gliomas results from the combined effect of epigenetic and genetic aberrations.

    Directory of Open Access Journals (Sweden)

    João Ramalho-Carvalho

    Full Text Available MGMT downregulation in high-grade gliomas (HGG has been mostly attributed to aberrant promoter methylation and is associated with increased sensitivity to alkylating agent-based chemotherapy. However, HGG harboring 10q deletions also benefit from treatment with alkylating agents. Because the MGMT gene is mapped at 10q26, we hypothesized that both epigenetic and genetic alterations might affect its expression and predict response to chemotherapy. To test this hypothesis, promoter methylation and mRNA levels of MGMT were determined by quantitative methylation-specific PCR (qMSP or methylation-specific multiplex ligation dependent probe amplification (MS-MLPA and quantitative RT-PCR, respectively, in a retrospective series of 61 HGG. MGMT/chromosome 10 copy number variations were determined by FISH or MS-MLPA analysis. Molecular findings were correlated with clinical parameters to assess their predictive value. Overall, MGMT methylation ratios assessed by qMSP and MS-MLPA were inversely correlated with mRNA expression levels (best coefficient value obtained with MS-MLPA. By FISH analysis in 68.3% of the cases there was loss of 10q26.1 and in 15% of the cases polysomy was demonstrated; the latter displayed the highest levels of transcript. When genetic and epigenetic data were combined, cases with MGMT promoter methylation and MGMT loss depicted the lowest transcript levels, although an impact in response to alkylating agent chemotherapy was not apparent. Cooperation between epigenetic (promoter methylation and genetic (monosomy, locus deletion changes affecting MGMT in HGG is required for effective MGMT silencing. Hence, evaluation of copy number alterations might add relevant prognostic and predictive information concerning response to alkylating agent-based chemotherapy.

  17. Genetic Variant in Flavin-Containing Monooxygenase 3 Alters Lipid Metabolism in Laying Hens in a Diet-Specific Manner

    OpenAIRE

    Wang, Jing; Long, Cheng; Zhang, Haijun; Zhang, Yanan; Wang, Hao; Yue, Hongyuan; Wang, Xiaocui; Wu, Shugeng; Qi, Guanghai

    2016-01-01

    Genetic variant T329S in flavin-containing monooxygenase 3 (FMO3) impairs trimethylamine (TMA) metabolism in birds. The TMA metabolism that under complex genetic and dietary regulation, closely linked to cardiovascular disease risk. We determined whether the genetic defects in TMA metabolism may change other metabolic traits in birds, determined whether the genetic effects depend on diets, and to identify genes or gene pathways that underlie the metabolic alteration induced by genetic and die...

  18. Generation of Infectious Poliovirus with Altered Genetic Information from Cloned cDNA.

    Science.gov (United States)

    Bujaki, Erika

    2016-01-01

    The effect of specific genetic alterations on virus biology and phenotype can be studied by a great number of available assays. The following method describes the basic protocol to generate infectious poliovirus with altered genetic information from cloned cDNA in cultured cells.The example explained here involves generation of a recombinant poliovirus genome by simply replacing a portion of the 5' noncoding region with a synthetic gene by restriction cloning. The vector containing the full length poliovirus genome and the insert DNA with the known mutation(s) are cleaved for directional cloning, then ligated and transformed into competent bacteria. The recombinant plasmid DNA is then propagated in bacteria and transcribed to RNA in vitro before RNA transfection of cultured cells is performed. Finally, viral particles are recovered from the cell culture.

  19. Whole-genome and Transcriptome Sequencing of Prostate Cancer Identify New Genetic Alterations Driving Disease Progression

    DEFF Research Database (Denmark)

    Ren, Shancheng; Wei, Gong-Hong; Liu, Dongbing

    2018-01-01

    BACKGROUND: Global disparities in prostate cancer (PCa) incidence highlight the urgent need to identify genomic abnormalities in prostate tumors in different ethnic populations including Asian men. OBJECTIVE: To systematically explore the genomic complexity and define disease-driven genetic......-scale and comprehensive genomic data of prostate cancer from Asian population. Identification of these genetic alterations may help advance prostate cancer diagnosis, prognosis, and treatment....... alterations in PCa. DESIGN, SETTING, AND PARTICIPANTS: The study sequenced whole-genome and transcriptome of tumor-benign paired tissues from 65 treatment-naive Chinese PCa patients. Subsequent targeted deep sequencing of 293 PCa-relevant genes was performed in another cohort of 145 prostate tumors. OUTCOME...

  20. Tissue culture-induced genetic and epigenetic alterations in rice pure-lines, F1 hybrids and polyploids.

    Science.gov (United States)

    Wang, Xiaoran; Wu, Rui; Lin, Xiuyun; Bai, Yan; Song, Congdi; Yu, Xiaoming; Xu, Chunming; Zhao, Na; Dong, Yuzhu; Liu, Bao

    2013-05-05

    Genetic and epigenetic alterations can be invoked by plant tissue culture, which may result in heritable changes in phenotypes, a phenomenon collectively termed somaclonal variation. Although extensive studies have been conducted on the molecular nature and spectrum of tissue culture-induced genomic alterations, the issue of whether and to what extent distinct plant genotypes, e.g., pure-lines, hybrids and polyploids, may respond differentially to the tissue culture condition remains poorly understood. We investigated tissue culture-induced genetic and epigenetic alterations in a set of rice genotypes including two pure-lines (different subspecies), a pair of reciprocal F1 hybrids parented by the two pure-lines, and a pair of reciprocal tetraploids resulted from the hybrids. Using two molecular markers, amplified fragment length polymorphism (AFLP) and methylation-sensitive amplified polymorphism (MSAP), both genetic and DNA methylation alterations were detected in calli and regenerants from all six genotypes, but genetic alteration is more prominent than epigenetic alteration. While significant genotypic difference was observed in frequencies of both types of alterations, only genetic alteration showed distinctive features among the three types of genomes, with one hybrid (N/9) being exceptionally labile. Surprisingly, difference in genetic alteration frequencies between the pair of reciprocal F1 hybrids is much greater than that between the two pure-line subspecies. Difference also exists in the pair of reciprocal tetraploids, but is to a less extent than that between the hybrids. The steady-state transcript abundance of genes involved in DNA repair and DNA methylation was significantly altered in both calli and regenerants, and some of which were correlated with the genetic and/or epigenetic alterations. Our results, based on molecular marker analysis of ca. 1,000 genomic loci, document that genetic alteration is the major cause of somaclonal variation in rice

  1. Phytoplasmal infection derails genetically preprogrammed meristem fate and alters plant architecture

    OpenAIRE

    Wei, Wei; Davis, Robert Edward; Nuss, Donald L.; Zhao, Yan

    2013-01-01

    In higher plants, the destiny of apical meristems (stem cells) is specific organogenesis, which determines the pattern of plant growth, and therefore morphotype and fertility. We found that bacterial infection can derail the meristems from their genetically preprogrammed destiny, altering plant morphogenesis. We identified four abnormal growth patterns, symptoms, in tomato infected with a cell wall-less bacterium, and found that each symptom corresponds to a distinct phase in meristem fate de...

  2. Genetic Alterations of the Thrombopoietin/MPL/JAK2 Axis Impacting Megakaryopoiesis

    OpenAIRE

    Plo, Isabelle; Bellanné-Chantelot, Christine; Mosca, Matthieu; Mazzi, Stefania; Marty, Caroline; Vainchenker, William

    2017-01-01

    Megakaryopoiesis is an original and complex cell process which leads to the formation of platelets. The homeostatic production of platelets is mainly regulated and controlled by thrombopoietin (TPO) and the TPO receptor (MPL)/JAK2 axis. Therefore, any hereditary or acquired abnormality affecting this signaling axis can result in thrombocytosis or thrombocytopenia. Thrombocytosis can be due to genetic alterations that affect either the intrinsic MPL signaling through gain-of-function (GOF) act...

  3. Wind power prediction based on genetic neural network

    Science.gov (United States)

    Zhang, Suhan

    2017-04-01

    The scale of grid connected wind farms keeps increasing. To ensure the stability of power system operation, make a reasonable scheduling scheme and improve the competitiveness of wind farm in the electricity generation market, it's important to accurately forecast the short-term wind power. To reduce the influence of the nonlinear relationship between the disturbance factor and the wind power, the improved prediction model based on genetic algorithm and neural network method is established. To overcome the shortcomings of long training time of BP neural network and easy to fall into local minimum and improve the accuracy of the neural network, genetic algorithm is adopted to optimize the parameters and topology of neural network. The historical data is used as input to predict short-term wind power. The effectiveness and feasibility of the method is verified by the actual data of a certain wind farm as an example.

  4. Genetic Programming for Sea Level Predictions in an Island Environment

    Directory of Open Access Journals (Sweden)

    M.A. Ghorbani

    2010-03-01

    Full Text Available Accurate predictions of sea-level are important for geodetic applications, navigation, coastal, industrial and tourist activities. In the current work, the Genetic Programming (GP and artificial neural networks (ANNs were applied to forecast half-daily and daily sea-level variations from 12 hours to 5 days ahead. The measurements at the Cocos (Keeling Islands in the Indian Ocean were used for training and testing of the employed artificial intelligence techniques. A comparison was performed of the predictions from the GP model and the ANN simulations. Based on the comparison outcomes, it was found that the Genetic Programming approach can be successfully employed in forecasting of sea level variations.

  5. Plant interactions alter the predictions of metabolic scaling theory

    DEFF Research Database (Denmark)

    Lin, Yue; Berger, Uta; Grimm, Volker

    2013-01-01

    Metabolic scaling theory (MST) is an attempt to link physiological processes of individual organisms with macroecology. It predicts a power law relationship with an exponent of 24/3 between mean individual biomass and density during densitydependent mortality (self-thinning). Empirical tests have...... processes can scale up to the population level. MST, like thermodynamics or biomechanics, sets limits within which organisms can live and function, but there may be stronger limits determined by ecological interactions. In such cases MST will not be predictive....... of plant stand development that includes three elements: a model of individual plant growth based on MST, different modes of local competition (size-symmetric vs. -asymmetric), and different resource levels. Our model is consistent with the observed variation in the slopes of self-thinning trajectories...

  6. Plant interactions alter the predictions of metabolic scaling theory.

    Directory of Open Access Journals (Sweden)

    Yue Lin

    Full Text Available Metabolic scaling theory (MST is an attempt to link physiological processes of individual organisms with macroecology. It predicts a power law relationship with an exponent of -4/3 between mean individual biomass and density during density-dependent mortality (self-thinning. Empirical tests have produced variable results, and the validity of MST is intensely debated. MST focuses on organisms' internal physiological mechanisms but we hypothesize that ecological interactions can be more important in determining plant mass-density relationships induced by density. We employ an individual-based model of plant stand development that includes three elements: a model of individual plant growth based on MST, different modes of local competition (size-symmetric vs. -asymmetric, and different resource levels. Our model is consistent with the observed variation in the slopes of self-thinning trajectories. Slopes were significantly shallower than -4/3 if competition was size-symmetric. We conclude that when the size of survivors is influenced by strong ecological interactions, these can override predictions of MST, whereas when surviving plants are less affected by interactions, individual-level metabolic processes can scale up to the population level. MST, like thermodynamics or biomechanics, sets limits within which organisms can live and function, but there may be stronger limits determined by ecological interactions. In such cases MST will not be predictive.

  7. Image-based computational quantification and visualization of genetic alterations and tumour heterogeneity.

    Science.gov (United States)

    Zhong, Qing; Rüschoff, Jan H; Guo, Tiannan; Gabrani, Maria; Schüffler, Peter J; Rechsteiner, Markus; Liu, Yansheng; Fuchs, Thomas J; Rupp, Niels J; Fankhauser, Christian; Buhmann, Joachim M; Perner, Sven; Poyet, Cédric; Blattner, Miriam; Soldini, Davide; Moch, Holger; Rubin, Mark A; Noske, Aurelia; Rüschoff, Josef; Haffner, Michael C; Jochum, Wolfram; Wild, Peter J

    2016-04-07

    Recent large-scale genome analyses of human tissue samples have uncovered a high degree of genetic alterations and tumour heterogeneity in most tumour entities, independent of morphological phenotypes and histopathological characteristics. Assessment of genetic copy-number variation (CNV) and tumour heterogeneity by fluorescence in situ hybridization (ISH) provides additional tissue morphology at single-cell resolution, but it is labour intensive with limited throughput and high inter-observer variability. We present an integrative method combining bright-field dual-colour chromogenic and silver ISH assays with an image-based computational workflow (ISHProfiler), for accurate detection of molecular signals, high-throughput evaluation of CNV, expressive visualization of multi-level heterogeneity (cellular, inter- and intra-tumour heterogeneity), and objective quantification of heterogeneous genetic deletions (PTEN) and amplifications (19q12, HER2) in diverse human tumours (prostate, endometrial, ovarian and gastric), using various tissue sizes and different scanners, with unprecedented throughput and reproducibility.

  8. Population genetic dynamics of three-spined sticklebacks (Gasterosteus aculeatus) in anthropogenic altered habitats.

    Science.gov (United States)

    Scharsack, Joern P; Schweyen, Hannah; Schmidt, Alexander M; Dittmar, Janine; Reusch, Thorsten Bh; Kurtz, Joachim

    2012-06-01

    In industrialized and/or agriculturally used landscapes, inhabiting species are exposed to a variety of anthropogenic changes in their environments. Genetic diversity may be reduced if populations encounter founder events, bottlenecks, or isolation. Conversely, genetic diversity may increase if populations adapt to changes in selective regimes in newly created habitats. With the present study, genetic variability of 918 sticklebacks from 43 samplings (21.3 ± 3.8 per sample) at 36 locations from cultivated landscapes in Northwest Germany was analyzed at nine neutral microsatellite loci. To test if differentiation is influenced by habitat alterations, sticklebacks were collected from ancient running waters and adjacent artificial stagnant waters, from brooks with salt water inflow of anthropogenic and natural origin and adjacent freshwater sites. Overall population structure was dominated by isolation by distance (IBD), which was significant across all populations, and analysis of molecular variance (AMOVA) revealed that 10.6% of the variation was explained by river catchment area. Populations in anthropogenic modified habitats deviated from the general IBD structure and in the AMOVA, grouping by habitat type running/stagnant water explained 4.9% of variation and 1.4% of the variation was explained by salt-/freshwater habitat. Sticklebacks in salt-polluted water systems seem to exhibit elevated migratory activity between fresh- and saltwater habitats, reducing IBD. In other situations, populations showed distinct signs of genetic isolation, which in some locations was attributed to mechanical migration barriers, but in others to potential anthropogenic induced bottleneck or founder effects. The present study shows that anthropogenic habitat alterations may have diverse effects on the population genetic structure of inhabiting species. Depending on the type of habitat change, increased genetic differentiation, diversification, or isolation are possible consequences.

  9. Shape: automatic conformation prediction of carbohydrates using a genetic algorithm

    Directory of Open Access Journals (Sweden)

    Rosen Jimmy

    2009-09-01

    Full Text Available Abstract Background Detailed experimental three dimensional structures of carbohydrates are often difficult to acquire. Molecular modelling and computational conformation prediction are therefore commonly used tools for three dimensional structure studies. Modelling procedures generally require significant training and computing resources, which is often impractical for most experimental chemists and biologists. Shape has been developed to improve the availability of modelling in this field. Results The Shape software package has been developed for simplicity of use and conformation prediction performance. A trivial user interface coupled to an efficient genetic algorithm conformation search makes it a powerful tool for automated modelling. Carbohydrates up to a few hundred atoms in size can be investigated on common computer hardware. It has been shown to perform well for the prediction of over four hundred bioactive oligosaccharides, as well as compare favourably with previously published studies on carbohydrate conformation prediction. Conclusion The Shape fully automated conformation prediction can be used by scientists who lack significant modelling training, and performs well on computing hardware such as laptops and desktops. It can also be deployed on computer clusters for increased capacity. The prediction accuracy under the default settings is good, as it agrees well with experimental data and previously published conformation prediction studies. This software is available both as open source and under commercial licenses.

  10. Genetic prediction of type 2 diabetes using deep neural network.

    Science.gov (United States)

    Kim, J; Kim, J; Kwak, M J; Bajaj, M

    2018-04-01

    Type 2 diabetes (T2DM) has strong heritability but genetic models to explain heritability have been challenging. We tested deep neural network (DNN) to predict T2DM using the nested case-control study of Nurses' Health Study (3326 females, 45.6% T2DM) and Health Professionals Follow-up Study (2502 males, 46.5% T2DM). We selected 96, 214, 399, and 678 single-nucleotide polymorphism (SNPs) through Fisher's exact test and L1-penalized logistic regression. We split each dataset randomly in 4:1 to train prediction models and test their performance. DNN and logistic regressions showed better area under the curve (AUC) of ROC curves than the clinical model when 399 or more SNPs included. DNN was superior than logistic regressions in AUC with 399 or more SNPs in male and 678 SNPs in female. Addition of clinical factors consistently increased AUC of DNN but failed to improve logistic regressions with 214 or more SNPs. In conclusion, we show that DNN can be a versatile tool to predict T2DM incorporating large numbers of SNPs and clinical information. Limitations include a relatively small number of the subjects mostly of European ethnicity. Further studies are warranted to confirm and improve performance of genetic prediction models using DNN in different ethnic groups. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  11. Introgression from cultivated rice alters genetic structures of wild relative populations: implications for in situ conservation

    Science.gov (United States)

    Jin, Xin; Chen, Yu; Liu, Ping; Li, Chen; Cai, Xingxing; Rong, Jun

    2018-01-01

    Abstract Maintaining genetic integrity is essential for in situ and ex situ conservation of crop wild relative (CWR) species. However, introgression of crop alleles into CWR species/populations may change their genetic structure and diversity, resulting in more invasive weeds or, in contrast, the extinction of endangered populations. To determine crop-wild introgression and its consequences, we examined the genetic structure and diversity of six wild rice (Oryza rufipogon) populations under in situ conservation in China. Thirty-four simple sequence repeat (SSR) and 34 insertion/deletion markers were used to genotype the wild rice populations and two sets of rice cultivars (O. sativa), corresponding to the two types of molecular markers. Shared alleles and STRUCTURE analyses suggested a variable level of crop-wild introgression and admixture. Principal coordinates and cluster analyses indicated differentiation of wild rice populations, which was associated with the spatial distances to cultivated rice fields. The level of overall genetic diversity was comparable between wild rice populations and rice cultivars, but a great number of wild-specific alleles was detected in the wild populations. We conclude based on the results that crop-wild introgression can considerably alter the pattern of genetic structure and relationships of CWR populations. Appropriate measures should be taken for effective in situ conservation of CWR species under the scenario of crop-wild introgression. PMID:29308123

  12. Genetic Alterations in the Molecular Subtypes of Bladder Cancer: Illustration in the Cancer Genome Atlas Dataset.

    Science.gov (United States)

    Choi, Woonyoung; Ochoa, Andrea; McConkey, David J; Aine, Mattias; Höglund, Mattias; Kim, William Y; Real, Francisco X; Kiltie, Anne E; Milsom, Ian; Dyrskjøt, Lars; Lerner, Seth P

    2017-09-01

    Recent whole genome mRNA expression profiling studies revealed that bladder cancers can be grouped into molecular subtypes, some of which share clinical properties and gene expression patterns with the intrinsic subtypes of breast cancer and the molecular subtypes found in other solid tumors. The molecular subtypes in other solid tumors are enriched with specific mutations and copy number aberrations that are thought to underlie their distinct progression patterns, and biological and clinical properties. The availability of comprehensive genomic data from The Cancer Genome Atlas (TCGA) and other large projects made it possible to correlate the presence of DNA alterations with tumor molecular subtype membership. Our overall goal was to determine whether specific DNA mutations and/or copy number variations are enriched in specific molecular subtypes. We used the complete TCGA RNA-seq dataset and three different published classifiers developed by our groups to assign TCGA's bladder cancers to molecular subtypes, and examined the prevalence of the most common DNA alterations within them. We interpreted the results against the background of what was known from the published literature about the prevalence of these alterations in nonmuscle-invasive and muscle-invasive bladder cancers. The results confirmed that alterations involving RB1 and NFE2L2 were enriched in basal cancers, whereas alterations involving FGFR3 and KDM6A were enriched in luminal tumors. The results further reinforce the conclusion that the molecular subtypes of bladder cancer are distinct disease entities with specific genetic alterations. Our observation showed that some of subtype-enriched mutations and copy number aberrations are clinically actionable, which has direct implications for the clinical management of patients with bladder cancer. Copyright © 2017 European Association of Urology. Published by Elsevier B.V. All rights reserved.

  13. Precursors predicted by artificial neural networks for mass balance calculations: Quantifying hydrothermal alteration in volcanic rocks

    Science.gov (United States)

    Trépanier, Sylvain; Mathieu, Lucie; Daigneault, Réal; Faure, Stéphane

    2016-04-01

    This study proposes an artificial neural networks-based method for predicting the unaltered (precursor) chemical compositions of hydrothermally altered volcanic rock. The method aims at predicting precursor's major components contents (SiO2, FeOT, MgO, CaO, Na2O, and K2O). The prediction is based on ratios of elements generally immobile during alteration processes; i.e. Zr, TiO2, Al2O3, Y, Nb, Th, and Cr, which are provided as inputs to the neural networks. Multi-layer perceptron neural networks were trained on a large dataset of least-altered volcanic rock samples that document a wide range of volcanic rock types, tectonic settings and ages. The precursors thus predicted are then used to perform mass balance calculations. Various statistics were calculated to validate the predictions of precursors' major components, which indicate that, overall, the predictions are precise and accurate. For example, rank-based correlation coefficients were calculated to compare predicted and analysed values from a least-altered test dataset that had not been used to train the networks. Coefficients over 0.87 were obtained for all components, except for Na2O (0.77), indicating that predictions for alkali might be less performant. Also, predictions are performant for most volcanic rock compositions, except for ultra-K rocks. The proposed method provides an easy and rapid solution to the often difficult task of determining appropriate volcanic precursor compositions to rocks modified by hydrothermal alteration. It is intended for large volcanic rock databases and is most useful, for example, to mineral exploration performed in complex or poorly known volcanic settings. The method is implemented as a simple C++ console program.

  14. Towards a predictive theory for genetic regulatory networks

    Science.gov (United States)

    Tkacik, Gasper

    When cells respond to changes in the environment by regulating the expression levels of their genes, we often draw parallels between these biological processes and engineered information processing systems. One can go beyond this qualitative analogy, however, by analyzing information transmission in biochemical ``hardware'' using Shannon's information theory. Here, gene regulation is viewed as a transmission channel operating under restrictive constraints set by the resource costs and intracellular noise. We present a series of results demonstrating that a theory of information transmission in genetic regulatory circuits feasibly yields non-trivial, testable predictions. These predictions concern strategies by which individual gene regulatory elements, e.g., promoters or enhancers, read out their signals; as well as strategies by which small networks of genes, independently or in spatially coupled settings, respond to their inputs. These predictions can be quantitatively compared to the known regulatory networks and their function, and can elucidate how reproducible biological processes, such as embryonic development, can be orchestrated by networks built out of noisy components. Preliminary successes in the gap gene network of the fruit fly Drosophila indicate that a full ab initio theoretical prediction of a regulatory network is possible, a feat that has not yet been achieved for any real regulatory network. We end by describing open challenges on the path towards such a prediction.

  15. Genetic variants alter T-bet binding and gene expression in mucosal inflammatory disease.

    Directory of Open Access Journals (Sweden)

    Katrina Soderquest

    2017-02-01

    Full Text Available The polarization of CD4+ T cells into distinct T helper cell lineages is essential for protective immunity against infection, but aberrant T cell polarization can cause autoimmunity. The transcription factor T-bet (TBX21 specifies the Th1 lineage and represses alternative T cell fates. Genome-wide association studies have identified single nucleotide polymorphisms (SNPs that may be causative for autoimmune diseases. The majority of these polymorphisms are located within non-coding distal regulatory elements. It is considered that these genetic variants contribute to disease by altering the binding of regulatory proteins and thus gene expression, but whether these variants alter the binding of lineage-specifying transcription factors has not been determined. Here, we show that SNPs associated with the mucosal inflammatory diseases Crohn's disease, ulcerative colitis (UC and celiac disease, but not rheumatoid arthritis or psoriasis, are enriched at T-bet binding sites. Furthermore, we identify disease-associated variants that alter T-bet binding in vitro and in vivo. ChIP-seq for T-bet in individuals heterozygous for the celiac disease-associated SNPs rs1465321 and rs2058622 and the IBD-associated SNPs rs1551398 and rs1551399, reveals decreased binding to the minor disease-associated alleles. Furthermore, we show that rs1465321 is an expression quantitative trait locus (eQTL for the neighboring gene IL18RAP, with decreased T-bet binding associated with decreased expression of this gene. These results suggest that genetic polymorphisms may predispose individuals to mucosal autoimmune disease through alterations in T-bet binding. Other disease-associated variants may similarly act by modulating the binding of lineage-specifying transcription factors in a tissue-selective and disease-specific manner.

  16. Genetic and epigenetic alterations of the reduced folate carrier in untreated diffuse large B-cell lymphoma

    DEFF Research Database (Denmark)

    Kastrup, I.B.; Worm, J.; Ralfkiaer, E.

    2008-01-01

    The reduced folate carrier (RFC) is a transmembrane protein that mediates cellular uptake of reduced folates and antifolate drugs, including methotrexate (MTX). Acquired alterations of the RFC gene have been associated with resistance to MTX in cancer cell lines and primary osteosarcomas. Here, w...... with adverse outcome. In DLBCL, genetic and epigenetic alterations of RFC were detected at diagnosis in the absence of a selective MTX pressure, suggesting that these alterations may possibly contribute to the development of lymphoma Udgivelsesdato: 2008/1...

  17. Consumer preferences for the predictive genetic test for Alzheimer disease.

    Science.gov (United States)

    Huang, Ming-Yi; Huston, Sally A; Perri, Matthew

    2014-04-01

    The purpose of this study was to assess consumer preferences for predictive genetic testing for Alzheimer disease in the United States. A rating conjoint analysis was conducted using an anonymous online survey distributed by Qualtrics to a general population panel in April 2011 in the United States. The study design included three attributes: Accuracy (40%, 80%, and 100%), Treatment Availability (Cure is available/Drug for symptom relief but no cure), and Anonymity (Anonymous/Not anonymous). A total of 12 scenarios were used to elicit people's preference, assessed by an 11-point scale. The respondents also indicated their highest willingness-to-pay (WTP) for each scenario through open-ended questions. A total of 295 responses were collected over 4 days. The most important attribute for the aggregate model was Accuracy, contributing 64.73% to the preference rating. Treatment Availability and Anonymity contributed 20.72% and 14.59%, respectively, to the preference rating. The median WTP for the highest-rating scenario (Accuracy 100%, a cure is available, test result is anonymous) was $100 (mean = $276). The median WTP for the lowest-rating scenario (40% accuracy, no cure but drugs for symptom relief, not anonymous) was zero (mean = $34). The results of this study highlight attributes people find important when making the hypothetical decision to obtain an AD genetic test. These results should be of interests to policy makers, genetic test developers and health care providers.

  18. Do Staphylococcus epidermidis Genetic Clusters Predict Isolation Sources?

    Science.gov (United States)

    Tolo, Isaiah; Thomas, Jonathan C.; Fischer, Rebecca S. B.; Brown, Eric L.; Gray, Barry M.

    2016-01-01

    Staphylococcus epidermidis is a ubiquitous colonizer of human skin and a common cause of medical device-associated infections. The extent to which the population genetic structure of S. epidermidis distinguishes commensal from pathogenic isolates is unclear. Previously, Bayesian clustering of 437 multilocus sequence types (STs) in the international database revealed a population structure of six genetic clusters (GCs) that may reflect the species' ecology. Here, we first verified the presence of six GCs, including two (GC3 and GC5) with significant admixture, in an updated database of 578 STs. Next, a single nucleotide polymorphism (SNP) assay was developed that accurately assigned 545 (94%) of 578 STs to GCs. Finally, the hypothesis that GCs could distinguish isolation sources was tested by SNP typing and GC assignment of 154 isolates from hospital patients with bacteremia and those with blood culture contaminants and from nonhospital carriage. GC5 was isolated almost exclusively from hospital sources. GC1 and GC6 were isolated from all sources but were overrepresented in isolates from nonhospital and infection sources, respectively. GC2, GC3, and GC4 were relatively rare in this collection. No association was detected between fdh-positive isolates (GC2 and GC4) and nonhospital sources. Using a machine learning algorithm, GCs predicted hospital and nonhospital sources with 80% accuracy and predicted infection and contaminant sources with 45% accuracy, which was comparable to the results seen with a combination of five genetic markers (icaA, IS256, sesD [bhp], mecA, and arginine catabolic mobile element [ACME]). Thus, analysis of population structure with subgenomic data shows the distinction of hospital and nonhospital sources and the near-inseparability of sources within a hospital. PMID:27076664

  19. Production of extracellular nucleic acids by genetically altered bacteria in aquatic-environment microcosms

    International Nuclear Information System (INIS)

    Paul, J.H.; David, A.W.

    1989-01-01

    The factors which affect the production of extracellular DNA by genetically altered strains of Escherichia coli, Pseudomonas aeruginosa, Pseudomonas cepacia, and Bradyrhizobium japonicum in aquatic environments were investigated. Cellular nucleic acids were labeled in vivo by incubation with [ 3 H]thymidine or [ 3 H]adenine, and production of extracellular DNA in marine waters, artificial seawater, or minimal salts media was determined by detecting radiolabeled macromolecules in incubation filtrates. The presence or absence of the ambient microbial community had little effect on the production of extracellular DNA. Three of four organisms produced the greatest amounts of extracellular nucleic acids when incubated in low-salinity media (2% artificial seawater) rather than high-salinity media (10 to 50% artificial seawater). The greatest production of extracellular nucleic acids by P. cepacia occurred at pH 7 and 37 degree C, suggesting that extracellular-DNA production may be a normal physiologic function of the cell. Incubation of labeled P. cepacia cells in water from Bimini Harbor, Bahamas, resulted in labeling of macromolecules of the ambient microbial population. Collectively these results indicate that (i) extracellular-DNA production by genetically altered bacteria released into aquatic environments is more strongly influenced by physicochemical factors than biotic factors, (ii) extracellular-DNA production rates are usually greater for organisms released in freshwater than marine environments, and (iii) ambient microbial populations can readily utilize materials released by these organisms

  20. The Landscape of Somatic Genetic Alterations in Breast Cancers From ATM Germline Mutation Carriers.

    Science.gov (United States)

    Weigelt, Britta; Bi, Rui; Kumar, Rahul; Blecua, Pedro; Mandelker, Diana L; Geyer, Felipe C; Pareja, Fresia; James, Paul A; Couch, Fergus J; Eccles, Diana M; Blows, Fiona; Pharoah, Paul; Li, Anqi; Selenica, Pier; Lim, Raymond S; Jayakumaran, Gowtham; Waddell, Nic; Shen, Ronglai; Norton, Larry; Wen, Hannah Y; Powell, Simon N; Riaz, Nadeem; Robson, Mark E; Reis-Filho, Jorge S; Chenevix-Trench, Georgia

    2018-02-28

    Pathogenic germline variants in ataxia-telangiectasia mutated (ATM), a gene that plays a role in DNA damage response and cell cycle checkpoints, confer an increased breast cancer (BC) risk. Here, we investigated the phenotypic characteristics and landscape of somatic genetic alterations in 24 BCs from ATM germline mutation carriers by whole-exome and targeted sequencing. ATM-associated BCs were consistently hormone receptor positive and largely displayed minimal immune infiltrate. Although 79.2% of these tumors exhibited loss of heterozygosity of the ATM wild-type allele, none displayed high activity of mutational signature 3 associated with defective homologous recombination DNA (HRD) repair. No TP53 mutations were found in the ATM-associated BCs. Analysis of an independent data set confirmed that germline ATM variants and TP53 somatic mutations are mutually exclusive. Our findings indicate that ATM-associated BCs often harbor bi-allelic inactivation of ATM, are phenotypically distinct from BRCA1/2-associated BCs, lack HRD-related mutational signatures, and that TP53 and ATM genetic alterations are likely epistatic.

  1. Genetic and metabolic signals during acute enteric bacterial infection alter the microbiota and drive progression to chronic inflammatory disease

    Energy Technology Data Exchange (ETDEWEB)

    Kamdar, Karishma; Khakpour, Samira; Chen, Jingyu; Leone, Vanessa; Brulc, Jennifer; Mangatu, Thomas; Antonopoulos, Dionysios A.; Chang, Eugene B; Kahn, Stacy A.; Kirschner, Barbara S; Young, Glenn; DePaolo, R. William

    2016-01-13

    Chronic inflammatory disorders are thought to arise due to an interplay between predisposing host genetics and environmental factors. For example, the onset of inflammatory bowel disease is associated with enteric proteobacterial infection, yet the mechanistic basis for this association is unclear. We have shown previously that genetic defiency in TLR1 promotes acute enteric infection by the proteobacteria Yersinia enterocolitica. Examining that model further, we uncovered an altered cellular immune response that promotes the recruitment of neutrophils which in turn increases metabolism of the respiratory electron acceptor tetrathionate by Yersinia. These events drive permanent alterations in anti-commensal immunity, microbiota composition, and chronic inflammation, which persist long after Yersinia clearence. Deletion of the bacterial genes involved in tetrathionate respiration or treatment using targeted probiotics could prevent microbiota alterations and inflammation. Thus, acute infection can drive long term immune and microbiota alterations leading to chronic inflammatory disease in genetically predisposed individuals.

  2. Histologic and biochemical alterations predict pulmonary mechanical dysfunction in aging mice with chronic lung inflammation.

    Science.gov (United States)

    Massa, Christopher B; Groves, Angela M; Jaggernauth, Smita U; Laskin, Debra L; Gow, Andrew J

    2017-08-01

    Both aging and chronic inflammation produce complex structural and biochemical alterations to the lung known to impact work of breathing. Mice deficient in surfactant protein D (Sftpd) develop progressive age-related lung pathology characterized by tissue destruction/remodeling, accumulation of foamy macrophages and alteration in surfactant composition. This study proposes to relate changes in tissue structure seen in normal aging and in chronic inflammation to altered lung mechanics using a computational model. Alterations in lung function in aging and Sftpd -/- mice have been inferred from fitting simple mechanical models to respiratory impedance data (Zrs), however interpretation has been confounded by the simultaneous presence of multiple coexisting pathophysiologic processes. In contrast to the inverse modeling approach, this study uses simulation from experimental measurements to recapitulate how aging and inflammation alter Zrs. Histologic and mechanical measurements were made in C57BL6/J mice and congenic Sftpd-/- mice at 8, 27 and 80 weeks of age (n = 8/group). An anatomic computational model based on published airway morphometry was developed and Zrs was simulated between 0.5 and 20 Hz. End expiratory pressure dependent changes in airway caliber and recruitment were estimated from mechanical measurements. Tissue elements were simulated using the constant phase model of viscoelasticity. Baseline elastance distribution was estimated in 8-week-old wild type mice, and stochastically varied for each condition based on experimentally measured alteration in elastic fiber composition, alveolar geometry and surfactant composition. Weighing reduction in model error against increasing model complexity allowed for identification of essential features underlying mechanical pathology and their contribution to Zrs. Using a maximum likelihood approach, alteration in lung recruitment and diminished elastic fiber density were shown predictive of mechanical alteration at

  3. Histologic and biochemical alterations predict pulmonary mechanical dysfunction in aging mice with chronic lung inflammation.

    Directory of Open Access Journals (Sweden)

    Christopher B Massa

    2017-08-01

    Full Text Available Both aging and chronic inflammation produce complex structural and biochemical alterations to the lung known to impact work of breathing. Mice deficient in surfactant protein D (Sftpd develop progressive age-related lung pathology characterized by tissue destruction/remodeling, accumulation of foamy macrophages and alteration in surfactant composition. This study proposes to relate changes in tissue structure seen in normal aging and in chronic inflammation to altered lung mechanics using a computational model. Alterations in lung function in aging and Sftpd -/- mice have been inferred from fitting simple mechanical models to respiratory impedance data (Zrs, however interpretation has been confounded by the simultaneous presence of multiple coexisting pathophysiologic processes. In contrast to the inverse modeling approach, this study uses simulation from experimental measurements to recapitulate how aging and inflammation alter Zrs. Histologic and mechanical measurements were made in C57BL6/J mice and congenic Sftpd-/- mice at 8, 27 and 80 weeks of age (n = 8/group. An anatomic computational model based on published airway morphometry was developed and Zrs was simulated between 0.5 and 20 Hz. End expiratory pressure dependent changes in airway caliber and recruitment were estimated from mechanical measurements. Tissue elements were simulated using the constant phase model of viscoelasticity. Baseline elastance distribution was estimated in 8-week-old wild type mice, and stochastically varied for each condition based on experimentally measured alteration in elastic fiber composition, alveolar geometry and surfactant composition. Weighing reduction in model error against increasing model complexity allowed for identification of essential features underlying mechanical pathology and their contribution to Zrs. Using a maximum likelihood approach, alteration in lung recruitment and diminished elastic fiber density were shown predictive of mechanical

  4. Genetic risk prediction and neurobiological understanding of alcoholism.

    Science.gov (United States)

    Levey, D F; Le-Niculescu, H; Frank, J; Ayalew, M; Jain, N; Kirlin, B; Learman, R; Winiger, E; Rodd, Z; Shekhar, A; Schork, N; Kiefer, F; Kiefe, F; Wodarz, N; Müller-Myhsok, B; Dahmen, N; Nöthen, M; Sherva, R; Farrer, L; Smith, A H; Kranzler, H R; Rietschel, M; Gelernter, J; Niculescu, A B

    2014-05-20

    We have used a translational Convergent Functional Genomics (CFG) approach to discover genes involved in alcoholism, by gene-level integration of genome-wide association study (GWAS) data from a German alcohol dependence cohort with other genetic and gene expression data, from human and animal model studies, similar to our previous work in bipolar disorder and schizophrenia. A panel of all the nominally significant P-value SNPs in the top candidate genes discovered by CFG  (n=135 genes, 713 SNPs) was used to generate a genetic  risk prediction score (GRPS), which showed a trend towards significance (P=0.053) in separating  alcohol dependent individuals from controls in an independent German test cohort. We then validated and prioritized our top findings from this discovery work, and subsequently tested them in three independent cohorts, from two continents. A panel of all the nominally significant P-value single-nucleotide length polymorphisms (SNPs) in the top candidate genes discovered by CFG (n=135 genes, 713 SNPs) were used to generate a Genetic Risk Prediction Score (GRPS), which showed a trend towards significance (P=0.053) in separating alcohol-dependent individuals from controls in an independent German test cohort. In order to validate and prioritize the key genes that drive behavior without some of the pleiotropic environmental confounds present in humans, we used a stress-reactive animal model of alcoholism developed by our group, the D-box binding protein (DBP) knockout mouse, consistent with the surfeit of stress theory of addiction proposed by Koob and colleagues. A much smaller panel (n=11 genes, 66 SNPs) of the top CFG-discovered genes for alcoholism, cross-validated and prioritized by this stress-reactive animal model showed better predictive ability in the independent German test cohort (P=0.041). The top CFG scoring gene for alcoholism from the initial discovery step, synuclein alpha (SNCA) remained the top gene after the stress

  5. Neural networks for predicting breeding values and genetic gains

    Directory of Open Access Journals (Sweden)

    Gabi Nunes Silva

    2014-12-01

    Full Text Available Analysis using Artificial Neural Networks has been described as an approach in the decision-making process that, although incipient, has been reported as presenting high potential for use in animal and plant breeding. In this study, we introduce the procedure of using the expanded data set for training the network. Wealso proposed using statistical parameters to estimate the breeding value of genotypes in simulated scenarios, in addition to the mean phenotypic value in a feed-forward back propagation multilayer perceptron network. After evaluating artificial neural network configurations, our results showed its superiority to estimates based on linear models, as well as its applicability in the genetic value prediction process. The results further indicated the good generalization performance of the neural network model in several additional validation experiments.

  6. Reliable prediction of adsorption isotherms via genetic algorithm molecular simulation.

    Science.gov (United States)

    LoftiKatooli, L; Shahsavand, A

    2017-01-01

    Conventional molecular simulation techniques such as grand canonical Monte Carlo (GCMC) strictly rely on purely random search inside the simulation box for predicting the adsorption isotherms. This blind search is usually extremely time demanding for providing a faithful approximation of the real isotherm and in some cases may lead to non-optimal solutions. A novel approach is presented in this article which does not use any of the classical steps of the standard GCMC method, such as displacement, insertation, and removal. The new approach is based on the well-known genetic algorithm to find the optimal configuration for adsorption of any adsorbate on a structured adsorbent under prevailing pressure and temperature. The proposed approach considers the molecular simulation problem as a global optimization challenge. A detailed flow chart of our so-called genetic algorithm molecular simulation (GAMS) method is presented, which is entirely different from traditions molecular simulation approaches. Three real case studies (for adsorption of CO 2 and H 2 over various zeolites) are borrowed from literature to clearly illustrate the superior performances of the proposed method over the standard GCMC technique. For the present method, the average absolute values of percentage errors are around 11% (RHO-H 2 ), 5% (CHA-CO 2 ), and 16% (BEA-CO 2 ), while they were about 70%, 15%, and 40% for the standard GCMC technique, respectively.

  7. Ternary alloy material prediction using genetic algorithm and cluster expansion

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Chong [Iowa State Univ., Ames, IA (United States)

    2015-12-01

    This thesis summarizes our study on the crystal structures prediction of Fe-V-Si system using genetic algorithm and cluster expansion. Our goal is to explore and look for new stable compounds. We started from the current ten known experimental phases, and calculated formation energies of those compounds using density functional theory (DFT) package, namely, VASP. The convex hull was generated based on the DFT calculations of the experimental known phases. Then we did random search on some metal rich (Fe and V) compositions and found that the lowest energy structures were body centered cube (bcc) underlying lattice, under which we did our computational systematic searches using genetic algorithm and cluster expansion. Among hundreds of the searched compositions, thirteen were selected and DFT formation energies were obtained by VASP. The stability checking of those thirteen compounds was done in reference to the experimental convex hull. We found that the composition, 24-8-16, i.e., Fe3VSi2 is a new stable phase and it can be very inspiring to the future experiments.

  8. Parkinson's disease and pesticides: A meta-analysis of disease connection and genetic alterations.

    Science.gov (United States)

    Ahmed, Hussien; Abushouk, Abdelrahman Ibrahim; Gabr, Mohamed; Negida, Ahmed; Abdel-Daim, Mohamed M

    2017-06-01

    Parkinson's disease (PD) is a globally prevalent, multifactorial disorder that occurs due to interactions between genetic and environmental factors. Observational studies have shown a link between exposure to pesticides and the risk of PD. We performed this study to systemically review published case-control studies and estimate quantitatively the association between pesticide exposure and PD. We searched Medline (through PubMed) for eligible case-control studies. The association between pesticide exposure and PD risk or occurrence of certain genetic alterations, related to the pathogenesis of PD was presented as odds ratios (OR) and pooled under the random effects model, using the statistical add-in (MetaXL, version 5.0). The pooled result showed that exposure to pesticides is linked to PD (OR 1.46, 95% CI [1.21, 1.77]), but there was a significant heterogeneity among included studies. Exposure to pesticides increased the risk of alterations in different PD pathogenesis-related genes, such as GST (OR 1.97, 95% CI [1.41, 2.76]), PON-1 (OR 1.32, 95% CI [1.09, 1.6]), MDR1 (OR 2.06, 95% CI [1.58, 2.68]), and SNCA genes (OR 1.28, 95% CI [1.02, 1.37]). There was no statistically significant association between exposure to pesticides and alteration of CYP2D6 (OR 1.19, 95% CI [0.91, 1.54]), SLC6A3 (OR 0.74, 95% CI [0.55, 1]), MnSOD (OR 1.45, 95% CI [0.97, 2.16]), NQO1 (OR 1.35, 95% CI [0.91, 2.01]), and PON-2 genes (OR 0.88, 95% CI [0.53, 1.45]). In conclusion, this meta-analysis provides evidence that pesticide exposure is significantly associated with the risk of PD and alterations in genes involved in PD pathogenesis. However, the underlying mechanism of this association and the effect of the duration of exposure or the type of pesticides should be addressed by future research. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

  9. New and emerging prognostic and predictive genetic biomarkers in B-cell precursor acute lymphoblastic leukemia

    Science.gov (United States)

    Moorman, Anthony V.

    2016-01-01

    Acute lymphoblastic leukemia (ALL) is a heterogeneous disease at the genetic level. Chromosomal abnormalities are used as diagnostic, prognostic and predictive biomarkers to provide subtype, outcome and drug response information. t(12;21)/ETV6-RUNX1 and high hyper-diploidy are good-risk prognostic biomarkers whereas KMT2A (MLL) translocations, t(17;19)/TCF3-HLF, haploidy or low hypodiploidy are high-risk biomarkers. t(9;22)/BCR-ABL1 patients require targeted treatment (imatinib/dasatinib), whereas iAMP21 patients achieve better outcomes when treated intensively. High-risk genetic biomarkers are four times more prevalent in adults compared to children. The application of genomic technologies to cases without an established abnormality (B-other) reveals copy number alterations which can be used either individually or in combination as prognostic biomarkers. Transcriptome sequencing studies have identified a network of fusion genes involving kinase genes - ABL1, ABL2, PDGFRB, CSF1R, CRLF2, JAK2 and EPOR. In vitro and in vivo studies along with emerging clinical observations indicate that patients with a kinase-activating aberration may respond to treatment with small molecular inhibitors like imatinib/dasatinib and ruxolitinib. Further work is required to determine the true frequency of these abnormalities across the age spectrum and the optimal way to incorporate such inhibitors into protocols. In conclusion, genetic biomarkers are playing an increasingly important role in the management of patients with ALL. PMID:27033238

  10. Transforming growth factor-β and breast cancer: Lessons learned from genetically altered mouse models

    International Nuclear Information System (INIS)

    Wakefield, Lalage M; Yang, Yu-an; Dukhanina, Oksana

    2000-01-01

    Transforming growth factor (TGF)-βs are plausible candidate tumor suppressors in the breast. They also have oncogenic activities under certain circumstances, however. Genetically altered mouse models provide powerful tools to analyze the complexities of TGF-βaction in the context of the whole animal. Overexpression of TGF-β can suppress tumorigenesis in the mammary gland, raising the possibility that use of pharmacologic agents to enhance TGF-β function locally might be an effective method for the chemoprevention of breast cancer. Conversely, loss of TGF-β response increases spontaneous and induced tumorigenesis in the mammary gland. This confirms that endogenous TGF-βs have tumor suppressor activity in the mammary gland, and suggests that the loss of TGF-β receptors seen in some human breast hyperplasias may play a causal role in tumor development

  11. Drug-induced and genetic alterations in stress-responsive systems: Implications for specific addictive diseases.

    Science.gov (United States)

    Zhou, Yan; Proudnikov, Dmitri; Yuferov, Vadim; Kreek, Mary Jeanne

    2010-02-16

    From the earliest work in our laboratory, we hypothesized, and with studies conducted in both clinical research and animal models, we have shown that drugs of abuse, administered or self-administered, on a chronic basis, profoundly alter stress-responsive systems. Alterations of expression of specific genes involved in stress responsivity, with increases or decreases in mRNA levels, receptor, and neuropeptide levels, and resultant changes in hormone levels, have been documented to occur after chronic intermittent exposure to heroin, morphine, other opiates, cocaine, other stimulants, and alcohol in animal models and in human molecular genetics. The best studied of the stress-responsive systems in humans and mammalian species in general is undoubtedly the HPA axis. In addition, there are stress-responsive systems in other parts in the brain itself, and some of these include components of the HPA axis, such as CRF and CRF receptors, along with POMC gene and gene products. Several other stress-responsive systems are known to influence the HPA axis, such as the vasopressin-vasopressin receptor system. Orexin-hypocretin, acting at its receptors, may effect changes which suggest that it should be properly categorized as a stress-responsive system. However, less is known about the interactions and connectivity of some of these different neuropeptide and receptor systems, and in particular, about the possible connectivity of fast-acting (e.g., glutamate and GABA) and slow-acting (including dopamine, serotonin, and norepinephrine) neurotransmitters with each of these stress-responsive components and the resultant impact, especially in the setting of chronic exposure to drugs of abuse. Several of these stress-responsive systems and components, primarily based on our laboratory-based and human molecular genetics research of addictive diseases, will be briefly discussed in this review. Copyright 2009 Elsevier B.V. All rights reserved.

  12. Targeted molecular profiling of rare genetic alterations in colorectal cancer using next-generation sequencing.

    Science.gov (United States)

    Jauhri, Mayank; Bhatnagar, Akanksha; Gupta, Satish; Shokeen, Yogender; Minhas, Sachin; Aggarwal, Shyam

    2016-10-01

    Mutation frequencies of common genetic alterations in colorectal cancer have been in the spotlight for many years. This study highlights few rare somatic mutations, which possess the attributes of a potential CRC biomarker yet are often neglected. Next-generation sequencing was performed over 112 tumor samples to detect genetic alterations in 31 rare genes in colorectal cancer. Mutations were detected in 26/31 (83.9 %) uncommon genes, which together contributed toward 149 gene mutations in 67/112 (59.8 %) colorectal cancer patients. The most frequent mutations include KDR (19.6 %), PTEN (17 %), FBXW7 (10.7 %), SMAD4 (10.7 %), VHL (8 %), KIT (8 %), MET (7.1 %), ATM (6.3 %), CTNNB1 (4.5 %) and CDKN2A (4.5 %). RB1, ERBB4 and ERBB2 mutations were persistent in 3.6 % patients. GNAS, FGFR2 and FGFR3 mutations were persistent in 1.8 % patients. Ten genes (EGFR, NOTCH1, SMARCB1, ABL1, STK11, SMO, RET, GNAQ, CSF1R and FLT3) were found mutated in 0.9 % patients. Lastly, no mutations were observed in AKT, HRAS, MAP2K1, PDGFR and JAK2. Significant associations were observed between VHL with tumor site, ERBB4 and SMARCB1 with tumor invasion, CTNNB1 with lack of lymph node involvement and CTNNB1, FGFR2 and FGFR3 with TNM stage. Significantly coinciding mutation pairs include PTEN and SMAD4, PTEN and KDR, EGFR and RET, EGFR and RB1, FBXW7 and CTNNB1, KDR and FGFR2, FLT3 and CTNNB1, RET and RB1, ATM and SMAD4, ATM and CDKN2A, ERBB4 and SMARCB1. This study elucidates few potential colorectal cancer biomarkers, specifically KDR, PTEN, FBXW7 and SMAD4, which are found mutated in more than 10 % patients.

  13. Distinct genetic alteration profiles of acute myeloid leukemia between Caucasian and Eastern Asian population.

    Science.gov (United States)

    Wei, Hui; Wang, Ying; Zhou, Chunlin; Lin, Dong; Liu, Bingcheng; Liu, Kaiqi; Qiu, Shaowei; Gong, Benfa; Li, Yan; Zhang, Guangji; Wei, Shuning; Gong, Xiaoyuan; Liu, Yuntao; Zhao, Xingli; Gu, Runxia; Mi, Yingchang; Wang, Jianxiang

    2018-02-10

    Racial and ethnic disparities in malignancies attract extensive attention. To investigate whether there are racial and ethnic disparities in genetic alteration between Caucasian and Eastern Asian population, data from several prospective AML trials were retrospectively analyzed in this study. We found that there were more patients with core binding factor (CBF) leukemia in Eastern Asian cohorts and there were different CBF leukemia constitutions between them. The ratios of CBF leukemia are 27.7, 22.1, 21.1, and 23.4%, respectively, in our (ChiCTR-TRC-10001202), another Chinese, Korean, and Japanese Eastern Asian cohorts, which are significantly higher than those in ECOG1900, MRC AML15, UK NCRI AML17, HOVON/SAKK AML-42, and German AML2003 (15.5, 12.5, 9.3, 10.2, and 12%, respectively). And CBFbeta-MYH11 occurred more prevalently in HOVON/SAKK AML- 42 and ECOG1900 trials (50.0 and 54.3% of CBF leukemia, respectively) than in Chinese and Japanese trials (20.1 and 20.8%, respectively). The proportion of FLT3-ITD mutation is 11.2% in our cohort, which is lower than that in MRC AML15 and UK NCRI AML17 (24.6 and 17.9%, respectively). Even after excluding the age bias, there are still different incidence rates of mutation between Caucasian and Eastern Asian population. These data suggest that there are racial and ethnic disparities in genetic alteration between Caucasian and Eastern Asian population.

  14. Genetic risk prediction and neurobiological understanding of alcoholism

    Science.gov (United States)

    Levey, D F; Le-Niculescu, H; Frank, J; Ayalew, M; Jain, N; Kirlin, B; Learman, R; Winiger, E; Rodd, Z; Shekhar, A; Schork, N; Kiefe, F; Wodarz, N; Müller-Myhsok, B; Dahmen, N; Nöthen, M; Sherva, R; Farrer, L; Smith, A H; Kranzler, H R; Rietschel, M; Gelernter, J; Niculescu, A B

    2014-01-01

    We have used a translational Convergent Functional Genomics (CFG) approach to discover genes involved in alcoholism, by gene-level integration of genome-wide association study (GWAS) data from a German alcohol dependence cohort with other genetic and gene expression data, from human and animal model studies, similar to our previous work in bipolar disorder and schizophrenia. A panel of all the nominally significant P-value SNPs in the top candidate genes discovered by CFG  (n=135 genes, 713 SNPs) was used to generate a genetic  risk prediction score (GRPS), which showed a trend towards significance (P=0.053) in separating  alcohol dependent individuals from controls in an independent German test cohort. We then validated and prioritized our top findings from this discovery work, and subsequently tested them in three independent cohorts, from two continents. In order to validate and prioritize the key genes that drive behavior without some of the pleiotropic environmental confounds present in humans, we used a stress-reactive animal model of alcoholism developed by our group, the D-box binding protein (DBP) knockout mouse, consistent with the surfeit of stress theory of addiction proposed by Koob and colleagues. A much smaller panel (n=11 genes, 66 SNPs) of the top CFG-discovered genes for alcoholism, cross-validated and prioritized by this stress-reactive animal model showed better predictive ability in the independent German test cohort (P=0.041). The top CFG scoring gene for alcoholism from the initial discovery step, synuclein alpha (SNCA) remained the top gene after the stress-reactive animal model cross-validation. We also tested this small panel of genes in two other independent test cohorts from the United States, one with alcohol dependence (P=0.00012) and one with alcohol abuse (a less severe form of alcoholism; P=0.0094). SNCA by itself was able to separate alcoholics from controls in the alcohol-dependent cohort (P=0.000013) and the alcohol abuse

  15. Genetic alterations of hepatocellular carcinoma by random amplified polymorphic DNA analysis and cloning sequencing of tumor differential DNA fragment

    Science.gov (United States)

    Xian, Zhi-Hong; Cong, Wen-Ming; Zhang, Shu-Hui; Wu, Meng-Chao

    2005-01-01

    AIM: To study the genetic alterations and their association with clinicopathological characteristics of hepatocellular carcinoma (HCC), and to find the tumor related DNA fragments. METHODS: DNA isolated from tumors and corresponding noncancerous liver tissues of 56 HCC patients was amplified by random amplified polymorphic DNA (RAPD) with 10 random 10-mer arbitrary primers. The RAPD bands showing obvious differences in tumor tissue DNA corresponding to that of normal tissue were separated, purified, cloned and sequenced. DNA sequences were analyzed and compared with GenBank data. RESULTS: A total of 56 cases of HCC were demonstrated to have genetic alterations, which were detected by at least one primer. The detestability of genetic alterations ranged from 20% to 70% in each case, and 17.9% to 50% in each primer. Serum HBV infection, tumor size, histological grade, tumor capsule, as well as tumor intrahepatic metastasis, might be correlated with genetic alterations on certain primers. A band with a higher intensity of 480 bp or so amplified fragments in tumor DNA relative to normal DNA could be seen in 27 of 56 tumor samples using primer 4. Sequence analysis of these fragments showed 91% homology with Homo sapiens double homeobox protein DUX10 gene. CONCLUSION: Genetic alterations are a frequent event in HCC, and tumor related DNA fragments have been found in this study, which may be associated with hepatocarcin-ogenesis. RAPD is an effective method for the identification and analysis of genetic alterations in HCC, and may provide new information for further evaluating the molecular mechanism of hepatocarcinogenesis. PMID:15996039

  16. Genetic Alterations of the Thrombopoietin/MPL/JAK2 Axis Impacting Megakaryopoiesis.

    Science.gov (United States)

    Plo, Isabelle; Bellanné-Chantelot, Christine; Mosca, Matthieu; Mazzi, Stefania; Marty, Caroline; Vainchenker, William

    2017-01-01

    Megakaryopoiesis is an original and complex cell process which leads to the formation of platelets. The homeostatic production of platelets is mainly regulated and controlled by thrombopoietin (TPO) and the TPO receptor (MPL)/JAK2 axis. Therefore, any hereditary or acquired abnormality affecting this signaling axis can result in thrombocytosis or thrombocytopenia. Thrombocytosis can be due to genetic alterations that affect either the intrinsic MPL signaling through gain-of-function (GOF) activity ( MPL, JAK2, CALR ) and loss-of-function (LOF) activity of negative regulators ( CBL, LNK ) or the extrinsic MPL signaling by THPO GOF mutations leading to increased TPO synthesis. Alternatively, thrombocytosis may paradoxically result from mutations of MPL leading to an abnormal MPL trafficking, inducing increased TPO levels by alteration of its clearance. In contrast, thrombocytopenia can also result from LOF THPO or MPL mutations, which cause a complete defect in MPL trafficking to the cell membrane, impaired MPL signaling or stability, defects in the TPO/MPL interaction, or an absence of TPO production.

  17. Scientific reporting is suboptimal for aspects that characterize genetic risk prediction studies: a review of published articles based on the Genetic RIsk Prediction Studies statement.

    Science.gov (United States)

    Iglesias, Adriana I; Mihaescu, Raluca; Ioannidis, John P A; Khoury, Muin J; Little, Julian; van Duijn, Cornelia M; Janssens, A Cecile J W

    2014-05-01

    Our main objective was to raise awareness of the areas that need improvements in the reporting of genetic risk prediction articles for future publications, based on the Genetic RIsk Prediction Studies (GRIPS) statement. We evaluated studies that developed or validated a prediction model based on multiple DNA variants, using empirical data, and were published in 2010. A data extraction form based on the 25 items of the GRIPS statement was created and piloted. Forty-two studies met our inclusion criteria. Overall, more than half of the evaluated items (34 of 62) were reported in at least 85% of included articles. Seventy-seven percentage of the articles were identified as genetic risk prediction studies through title assessment, but only 31% used the keywords recommended by GRIPS in the title or abstract. Seventy-four percentage mentioned which allele was the risk variant. Overall, only 10% of the articles reported all essential items needed to perform external validation of the risk model. Completeness of reporting in genetic risk prediction studies is adequate for general elements of study design but is suboptimal for several aspects that characterize genetic risk prediction studies such as description of the model construction. Improvements in the transparency of reporting of these aspects would facilitate the identification, replication, and application of genetic risk prediction models. Copyright © 2014 Elsevier Inc. All rights reserved.

  18. Phenotype prediction using regularized regression on genetic data in the DREAM5 Systems Genetics B Challenge.

    Directory of Open Access Journals (Sweden)

    Po-Ru Loh

    Full Text Available A major goal of large-scale genomics projects is to enable the use of data from high-throughput experimental methods to predict complex phenotypes such as disease susceptibility. The DREAM5 Systems Genetics B Challenge solicited algorithms to predict soybean plant resistance to the pathogen Phytophthora sojae from training sets including phenotype, genotype, and gene expression data. The challenge test set was divided into three subcategories, one requiring prediction based on only genotype data, another on only gene expression data, and the third on both genotype and gene expression data. Here we present our approach, primarily using regularized regression, which received the best-performer award for subchallenge B2 (gene expression only. We found that despite the availability of 941 genotype markers and 28,395 gene expression features, optimal models determined by cross-validation experiments typically used fewer than ten predictors, underscoring the importance of strong regularization in noisy datasets with far more features than samples. We also present substantial analysis of the training and test setup of the challenge, identifying high variance in performance on the gold standard test sets.

  19. Effect of genetic architecture on the prediction accuracy of quantitative traits in samples of unrelated individuals.

    Science.gov (United States)

    Morgante, Fabio; Huang, Wen; Maltecca, Christian; Mackay, Trudy F C

    2018-06-01

    Predicting complex phenotypes from genomic data is a fundamental aim of animal and plant breeding, where we wish to predict genetic merits of selection candidates; and of human genetics, where we wish to predict disease risk. While genomic prediction models work well with populations of related individuals and high linkage disequilibrium (LD) (e.g., livestock), comparable models perform poorly for populations of unrelated individuals and low LD (e.g., humans). We hypothesized that low prediction accuracies in the latter situation may occur when the genetics architecture of the trait departs from the infinitesimal and additive architecture assumed by most prediction models. We used simulated data for 10,000 lines based on sequence data from a population of unrelated, inbred Drosophila melanogaster lines to evaluate this hypothesis. We show that, even in very simplified scenarios meant as a stress test of the commonly used Genomic Best Linear Unbiased Predictor (G-BLUP) method, using all common variants yields low prediction accuracy regardless of the trait genetic architecture. However, prediction accuracy increases when predictions are informed by the genetic architecture inferred from mapping the top variants affecting main effects and interactions in the training data, provided there is sufficient power for mapping. When the true genetic architecture is largely or partially due to epistatic interactions, the additive model may not perform well, while models that account explicitly for interactions generally increase prediction accuracy. Our results indicate that accounting for genetic architecture can improve prediction accuracy for quantitative traits.

  20. Evidence of Hippocampal Structural Alterations in Gulf War Veterans With Predicted Exposure to the Khamisiyah Plume.

    Science.gov (United States)

    Chao, Linda L; Raymond, Morgan R; Leo, Cynthia K; Abadjian, Linda R

    2017-10-01

    To replicate and expand our previous findings of smaller hippocampal volumes in Gulf War (GW) veterans with predicted exposure to the Khamisiyah plume. Total hippocampal and hippocampal subfield volumes were quantified from 3 Tesla magnetic resonance images in 113 GW veterans, 62 of whom had predicted exposure as per the Department of Defense exposure models. Veterans with predicted exposure had smaller total hippocampal and CA3/dentate gyrus volumes compared with unexposed veterans, even after accounting for potentially confounding genetic and clinical variables. Among veterans with predicted exposure, memory performance was positively correlated with hippocampal volume and negatively correlated with estimated exposure levels and self-reported memory difficulties. These results replicate and extend our previous finding that low-level exposure to chemical nerve agents from the Khamisiyah pit demolition has detrimental, lasting effects on brain structure and function.

  1. Thermal and hydrologic responses to climate change predict marked alterations in boreal stream invertebrate assemblages.

    Science.gov (United States)

    Mustonen, Kaisa-Riikka; Mykrä, Heikki; Marttila, Hannu; Sarremejane, Romain; Veijalainen, Noora; Sippel, Kalle; Muotka, Timo; Hawkins, Charles P

    2018-06-01

    Air temperature at the northernmost latitudes is predicted to increase steeply and precipitation to become more variable by the end of the 21st century, resulting in altered thermal and hydrological regimes. We applied five climate scenarios to predict the future (2070-2100) benthic macroinvertebrate assemblages at 239 near-pristine sites across Finland (ca. 1200 km latitudinal span). We used a multitaxon distribution model with air temperature and modeled daily flow as predictors. As expected, projected air temperature increased the most in northernmost Finland. Predicted taxonomic richness also increased the most in northern Finland, congruent with the predicted northwards shift of many species' distributions. Compositional changes were predicted to be high even without changes in richness, suggesting that species replacement may be the main mechanism causing climate-induced changes in macroinvertebrate assemblages. Northern streams were predicted to lose much of the seasonality of their flow regimes, causing potentially marked changes in stream benthic assemblages. Sites with the highest loss of seasonality were predicted to support future assemblages that deviate most in compositional similarity from the present-day assemblages. Macroinvertebrate assemblages were also predicted to change more in headwaters than in larger streams, as headwaters were particularly sensitive to changes in flow patterns. Our results emphasize the importance of focusing protection and mitigation on headwater streams with high-flow seasonality because of their vulnerability to climate change. © 2018 John Wiley & Sons Ltd.

  2. Narcissism predicts impulsive buying: phenotypic and genetic evidence

    Science.gov (United States)

    Cai, Huajian; Shi, Yuanyuan; Fang, Xiang; Luo, Yu L. L.

    2015-01-01

    Impulsive buying makes billions of dollars for retail businesses every year, particularly in an era of thriving e-commerce. Narcissism, characterized by impulsivity and materialism, may serve as a potential antecedent to impulsive buying. To test this hypothesis, two studies examined the relationship between narcissism and impulsive buying. In Study 1, we surveyed an online sample and found that while adaptive narcissism was not correlated with impulsive buying, maladaptive narcissism was significantly predictive of the impulsive buying tendency. By investigating 304 twin pairs, Study 2 showed that global narcissism and its two components, adaptive and maladaptive narcissism, as well as the impulsive buying tendency were heritable. The study found, moreover, that the connections between global narcissism and impulsive buying, and between maladaptive narcissism and impulsive buying were genetically based. These findings not only establish a link between narcissism and impulsive buying but also help to identify the origins of the link. The present studies deepen our understanding of narcissism, impulsive buying, and their interrelationship. PMID:26217251

  3. Narcissism predicts impulsive buying: phenotypic and genetic evidence.

    Science.gov (United States)

    Cai, Huajian; Shi, Yuanyuan; Fang, Xiang; Luo, Yu L L

    2015-01-01

    Impulsive buying makes billions of dollars for retail businesses every year, particularly in an era of thriving e-commerce. Narcissism, characterized by impulsivity and materialism, may serve as a potential antecedent to impulsive buying. To test this hypothesis, two studies examined the relationship between narcissism and impulsive buying. In Study 1, we surveyed an online sample and found that while adaptive narcissism was not correlated with impulsive buying, maladaptive narcissism was significantly predictive of the impulsive buying tendency. By investigating 304 twin pairs, Study 2 showed that global narcissism and its two components, adaptive and maladaptive narcissism, as well as the impulsive buying tendency were heritable. The study found, moreover, that the connections between global narcissism and impulsive buying, and between maladaptive narcissism and impulsive buying were genetically based. These findings not only establish a link between narcissism and impulsive buying but also help to identify the origins of the link. The present studies deepen our understanding of narcissism, impulsive buying, and their interrelationship.

  4. Flow discharge prediction in compound channels using linear genetic programming

    Science.gov (United States)

    Azamathulla, H. Md.; Zahiri, A.

    2012-08-01

    SummaryFlow discharge determination in rivers is one of the key elements in mathematical modelling in the design of river engineering projects. Because of the inundation of floodplains and sudden changes in river geometry, flow resistance equations are not applicable for compound channels. Therefore, many approaches have been developed for modification of flow discharge computations. Most of these methods have satisfactory results only in laboratory flumes. Due to the ability to model complex phenomena, the artificial intelligence methods have recently been employed for wide applications in various fields of water engineering. Linear genetic programming (LGP), a branch of artificial intelligence methods, is able to optimise the model structure and its components and to derive an explicit equation based on the variables of the phenomena. In this paper, a precise dimensionless equation has been derived for prediction of flood discharge using LGP. The proposed model was developed using published data compiled for stage-discharge data sets for 394 laboratories, and field of 30 compound channels. The results indicate that the LGP model has a better performance than the existing models.

  5. Narcissism predicts impulsive buying: phenotypic and genetic evidence

    Directory of Open Access Journals (Sweden)

    Huajian eCai

    2015-07-01

    Full Text Available Impulsive buying makes billions of dollars for retail businesses every year, particularly in an era of thriving e-commerce. Narcissism, characterized by impulsivity and materialism, may serve as a potential antecedent to impulsive buying. To test this hypothesis, two studies examined the relationship between narcissism and impulsive buying. In study 1, we surveyed narcissism and the impulsive buying tendency among an online sample and found that while adaptive narcissism was not correlated with impulsive buying, maladaptive narcissism was significantly predictive of the impulsive buying tendency. By investigating narcissism and the impulsive buying tendency in 304 twin pairs, study 2 showed that global narcissism and its two components, adaptive and maladaptive narcissism, as well as the impulsive buying tendency were heritable. The study found, moreover, that the connections between global narcissism and impulsive buying, and between maladaptive narcissism and impulsive buying were genetically based. These findings not only establish a link between narcissism and impulsive buying but also help to identify the origins of the link. The present studies deepen our understanding of narcissism, impulsive buying, and their interrelationship.

  6. Effects Of Hydrothermal Alteration On Magnetic Properties And Magnetic Signatures - Implications For Predictive Magnetic Exploration Models

    Science.gov (United States)

    Clark, D.

    2012-12-01

    Magnetics is the most widely used geophysical method in hard rock exploration and magnetic surveys are an integral part of exploration programs for many types of mineral deposit, including porphyry Cu, intrusive-related gold, volcanic-hosted epithermal Au, IOCG, VMS, and Ni sulfide deposits. However, the magnetic signatures of ore deposits and their associated mineralized systems are extremely variable and exploration that is based simply on searching for signatures that resemble those of known deposits and systems is rarely successful. Predictive magnetic exploration models are based upon well-established geological models, combined with magnetic property measurements and geological information from well-studied deposits, and guided by magnetic petrological understanding of the processes that create, destroy and modify magnetic minerals in rocks. These models are designed to guide exploration by predicting magnetic signatures that are appropriate to specific geological settings, taking into account factors such as tectonic province; protolith composition; post-formation tilting/faulting/ burial/ exhumation and partial erosion; and metamorphism. Patterns of zoned hydrothermal alteration are important indicators of potentially mineralized systems and, if properly interpreted, can provided vectors to ore. Magnetic signatures associated with these patterns at a range of scales can provide valuable information on prospectivity and can guide drilling, provided they are correctly interpreted in geological terms. This presentation reviews effects of the important types of hydrothermal alteration on magnetic properties within mineralized systems, with particular reference to porphyry copper and IOCG deposits. For example, an unmodified gold-rich porphyry copper system, emplaced into mafic-intermediate volcanic host rocks (such as Bajo de la Alumbrera, Argentina) exhibits an inner potassic zone that is strongly mineralized and magnetite-rich, which is surrounded by an outer

  7. Genetic alterations in lung cancer: Assessing limitations in routine clinical use

    Directory of Open Access Journals (Sweden)

    Joana Espiga Macedo

    2007-01-01

    Full Text Available Lung cancer is the most frequent cause of cancer mortality worldwide, responsible for approximately 1.1 million deaths per year. Median survival is short, both as most tumours are diagnosed at an advanced stage and because of the limited efficacy of available treatments. The development of tumour molecular genetics carries the promise of altering this state of affairs, as it should lead to a more precise classification of tumours, identify specific molecular targets for therapy and, above all, allow the development of new methods for early diagnosis. Despite numerous studies demonstrating the usefulness of molecular genetic techniques in the study of lung cancer, its routine clinical use in Portugal has, however, been limited.In this study, we used a p53 mutation screen in multiple clinical samples from a series of lung cancer patients to attempt to identify the main practical limitations to the integration of molecular genetics in routine clinical practice. Our results suggest that the main limiting factor is the availability of samples with good quality DNA; a problem that could be overcome by alterations in common sample collection and storage procedures. Resumo: O cancro do pulmão é a causa mais frequente de mortalidade por cancro no mundo, sendo responsável por cerca de 1,1 milhões de mortes por ano. A sobrevivência média dos doentes é geralmente curta, por a doença se encontrar em estádios avançados na altura do diagnóstico, mas também devido à falta de eficácia dos tratamentos disponíveis. O advento da genética molecular dos tumores trouxe consigo a possibilidade de modificar esta situação, quer através do refinamento do diagnóstico, quer da identificação de alvos terapêuticos específicos, quer sobretudo por – pelo menos em teoria – permitir o diagnóstico precoce da doença. No entanto, e apesar de numerosos trabalhos terem já demonstrado a utilidade

  8. Integrative analysis reveals relationships of genetic and epigenetic alterations in osteosarcoma.

    Directory of Open Access Journals (Sweden)

    Stine H Kresse

    Full Text Available BACKGROUND: Osteosarcomas are the most common non-haematological primary malignant tumours of bone, and all conventional osteosarcomas are high-grade tumours showing complex genomic aberrations. We have integrated genome-wide genetic and epigenetic profiles from the EuroBoNeT panel of 19 human osteosarcoma cell lines based on microarray technologies. PRINCIPAL FINDINGS: The cell lines showed complex patterns of DNA copy number changes, where genomic copy number gains were significantly associated with gene-rich regions and losses with gene-poor regions. By integrating the datasets, 350 genes were identified as having two types of aberrations (gain/over-expression, hypo-methylation/over-expression, loss/under-expression or hyper-methylation/under-expression using a recurrence threshold of 6/19 (>30% cell lines. The genes showed in general alterations in either DNA copy number or DNA methylation, both within individual samples and across the sample panel. These 350 genes are involved in embryonic skeletal system development and morphogenesis, as well as remodelling of extracellular matrix. The aberrations of three selected genes, CXCL5, DLX5 and RUNX2, were validated in five cell lines and five tumour samples using PCR techniques. Several genes were hyper-methylated and under-expressed compared to normal osteoblasts, and expression could be reactivated by demethylation using 5-Aza-2'-deoxycytidine treatment for four genes tested; AKAP12, CXCL5, EFEMP1 and IL11RA. Globally, there was as expected a significant positive association between gain and over-expression, loss and under-expression as well as hyper-methylation and under-expression, but gain was also associated with hyper-methylation and under-expression, suggesting that hyper-methylation may oppose the effects of increased copy number for detrimental genes. CONCLUSIONS: Integrative analysis of genome-wide genetic and epigenetic alterations identified dependencies and relationships between

  9. Hereditary kidney cancer syndromes: Genetic disorders driven by alterations in metabolism and epigenome regulation.

    Science.gov (United States)

    Hasumi, Hisashi; Yao, Masahiro

    2018-03-01

    Although hereditary kidney cancer syndrome accounts for approximately five percent of all kidney cancers, the mechanistic insight into tumor development in these rare conditions has provided the foundation for the development of molecular targeting agents currently used for sporadic kidney cancer. In the late 1980s, the comprehensive study for hereditary kidney cancer syndrome was launched in the National Cancer Institute, USA and the first kidney cancer-associated gene, VHL, was identified through kindred analysis of von Hippel-Lindau (VHL) syndrome in 1993. Subsequent molecular studies on VHL function have elucidated that the VHL protein is a component of E3 ubiquitin ligase complex for hypoxia-inducible factor (HIF), which provided the basis for the development of tyrosine kinase inhibitors targeting the HIF-VEGF/PDGF pathway. Recent whole-exome sequencing analysis of sporadic kidney cancer exhibited the recurrent mutations in chromatin remodeling genes and the later study has revealed that several chromatin remodeling genes are altered in kidney cancer kindred at the germline level. To date, more than 10 hereditary kidney cancer syndromes together with each responsible gene have been characterized and most of the causative genes for these genetic disorders are associated with either metabolism or epigenome regulation. In this review article, we describe the molecular mechanisms of how an alteration of each kidney cancer-associated gene leads to renal tumorigenesis as well as denote therapeutic targets elicited by studies on hereditary kidney cancer. © 2018 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association.

  10. Using human genetics to predict the effects and side-effects of drugs

    DEFF Research Database (Denmark)

    Stender, Stefan; Tybjærg-Hansen, Anne

    2016-01-01

    PURPOSE OF REVIEW: 'Genetic proxies' are increasingly being used to predict the effects of drugs. We present an up-to-date overview of the use of human genetics to predict effects and adverse effects of lipid-targeting drugs. RECENT FINDINGS: LDL cholesterol lowering variants in HMG-Coenzyme A re...

  11. Altered expression of HER-2 and the mismatch repair genes MLH1 and MSH2 predicts the outcome of T1 high-grade bladder cancer.

    Science.gov (United States)

    Sanguedolce, Francesca; Cormio, Antonella; Massenio, Paolo; Pedicillo, Maria C; Cagiano, Simona; Fortunato, Francesca; Calò, Beppe; Di Fino, Giuseppe; Carrieri, Giuseppe; Bufo, Pantaleo; Cormio, Luigi

    2018-04-01

    The identification of factors predicting the outcome of stage T1 high-grade bladder cancer (BC) is a major clinical issue. We performed immunohistochemistry to assess the role of human epidermal growth factor receptor-2 (HER-2) and microsatellite instability (MSI) factors MutL homologue 1 (MLH1) and MutS homologue 2 (MSH2) in predicting recurrence and progression of T1 high-grade BCs having undergone transurethral resection of bladder tumor (TURBT) alone or TURBT + intravesical instillations of bacillus Calmette-Guerin (BCG). HER-2 overexpression was a significant predictor of disease-free survival (DFS) in the overall as well as in the two patients' population; as for progression-free survival (PFS), it was significant in the overall but not in the two patients' population. MLH1 was an independent predictor of PFS only in patients treated with BCG and MSH2 failed to predict DFS and PFS in all populations. Most importantly, the higher the number of altered markers the lowers the DFS and PFS. In multivariate Cox proportional-hazards regression analysis, the number of altered molecular markers and BCG treatment were significant predictors (p = 0.0004 and 0.0283, respectively) of DFS, whereas the number of altered molecular markers was the only significant predictor (p = 0.0054) of PFS. Altered expression of the proto-oncogene HER-2 and the two molecular markers of genetic instability MLH1 and MSH2 predicted T1 high-grade BC outcome with the higher the number of altered markers the lower the DFS and PFS. These findings provide grounds for further testing them in predicting the outcome of this challenging disease.

  12. Joint modeling of genetically correlated diseases and functional annotations increases accuracy of polygenic risk prediction.

    Directory of Open Access Journals (Sweden)

    Yiming Hu

    2017-06-01

    Full Text Available Accurate prediction of disease risk based on genetic factors is an important goal in human genetics research and precision medicine. Advanced prediction models will lead to more effective disease prevention and treatment strategies. Despite the identification of thousands of disease-associated genetic variants through genome-wide association studies (GWAS in the past decade, accuracy of genetic risk prediction remains moderate for most diseases, which is largely due to the challenges in both identifying all the functionally relevant variants and accurately estimating their effect sizes. In this work, we introduce PleioPred, a principled framework that leverages pleiotropy and functional annotations in genetic risk prediction for complex diseases. PleioPred uses GWAS summary statistics as its input, and jointly models multiple genetically correlated diseases and a variety of external information including linkage disequilibrium and diverse functional annotations to increase the accuracy of risk prediction. Through comprehensive simulations and real data analyses on Crohn's disease, celiac disease and type-II diabetes, we demonstrate that our approach can substantially increase the accuracy of polygenic risk prediction and risk population stratification, i.e. PleioPred can significantly better separate type-II diabetes patients with early and late onset ages, illustrating its potential clinical application. Furthermore, we show that the increment in prediction accuracy is significantly correlated with the genetic correlation between the predicted and jointly modeled diseases.

  13. Predictive value of testing for multiple genetic variants in multifactorial

    NARCIS (Netherlands)

    A.C.J.W. Janssens (Cécile); M.J. Khoury (Muin Joseph)

    2009-01-01

    textabstractMultifactorial diseases such as type 2 diabetes, osteoporosis, and cardiovascular disease are caused by a complex interplay of many genetic and nongenetic factors, each of which conveys a minor increase in the risk of disease. Unraveling the genetic origins of these diseases is

  14. Genetic liability for schizophrenia predicts risk of immune disorders

    NARCIS (Netherlands)

    Stringer, Sven; Kahn, René S.; de Witte, Lot D.; Ophoff, Roel A.; Derks, Eske M.

    2014-01-01

    Schizophrenia patients and their parents have an increased risk of immune disorders compared to population controls and their parents. This may be explained by genetic overlap in the pathogenesis of both types of disorders. The purpose of this study was to investigate the genetic overlap between

  15. Genetic liability for schizophrenia predicts risk of immune disorders

    NARCIS (Netherlands)

    Stringer, Sven; Kahn, René S; de Witte, Lot D; Ophoff, Roel A; Derks, Eske M

    2014-01-01

    BACKGROUND: Schizophrenia patients and their parents have an increased risk of immune disorders compared to population controls and their parents. This may be explained by genetic overlap in the pathogenesis of both types of disorders. The purpose of this study was to investigate the genetic overlap

  16. Longitudinal Alterations of Frontoparietal and Frontotemporal Networks Predict Future Creative Cognitive Ability.

    Science.gov (United States)

    Chen, Qunlin; Beaty, Roger E; Wei, Dongtao; Yang, Junyi; Sun, Jiangzhou; Liu, Wei; Yang, Wenjing; Zhang, Qinglin; Qiu, Jiang

    2018-01-01

    Creative cognition is important to academic performance and career success during late adolescence and adulthood. However, there is a lack of longitudinal data on whether brain structural development could predict improvements in creative thinking, and how such changes interact with other cognitive abilities to support creative performance. Here we examined longitudinal alterations of brain structure and their relation to creative cognitive ability in a sample of 159 healthy young adults who were scanned using magnetic resonance imaging 2-3 times over the course of 3 years. The most robust predictor of future creative ability was the right dorsolateral prefrontal cortex (DLPFC), which in conjunction with baseline creative capacity showed a 31% prediction rate. Longitudinal analysis revealed that slower decreases in gray matter density within left frontoparietal and right frontotemporal clusters predicted enhanced creative ability. Moreoever, the relationship between longitudinal alterations within frontal-related clusters and improved creative ability was moderated by the right DLPFC and working memory ability. We conclude that continuous goal-directed planning and accumulated knowledge are implemented in the right DLPFC and temporal areas, respectively, which in turn support longitudinal gains in creative cognitive ability. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  17. Technology assessment and resource allocation for predictive genetic testing: A study of the perspectives of Canadian genetic health care providers

    Directory of Open Access Journals (Sweden)

    Einsiedel Edna

    2009-06-01

    Full Text Available Abstract Background With a growing number of genetic tests becoming available to the health and consumer markets, genetic health care providers in Canada are faced with the challenge of developing robust decision rules or guidelines to allocate a finite number of public resources. The objective of this study was to gain Canadian genetic health providers' perspectives on factors and criteria that influence and shape resource allocation decisions for publically funded predictive genetic testing in Canada. Methods The authors conducted semi-structured interviews with 16 senior lab directors and clinicians at publically funded Canadian predictive genetic testing facilities. Participants were drawn from British Columbia, Alberta, Manitoba, Ontario, Quebec and Nova Scotia. Given the community sampled was identified as being relatively small and challenging to access, purposive sampling coupled with snowball sampling methodologies were utilized. Results Surveyed lab directors and clinicians indicated that predictive genetic tests were funded provincially by one of two predominant funding models, but they themselves played a significant role in how these funds were allocated for specific tests and services. They also rated and identified several factors that influenced allocation decisions and patients' decisions regarding testing. Lastly, participants provided recommendations regarding changes to existing allocation models and showed support for a national evaluation process for predictive testing. Conclusion Our findings suggest that largely local and relatively ad hoc decision making processes are being made in relation to resource allocations for predictive genetic tests and that a more coordinated and, potentially, national approach to allocation decisions in this context may be appropriate.

  18. Predicting the natural flow regime: Models for assessing hydrological alteration in streams

    Science.gov (United States)

    Carlisle, D.M.; Falcone, J.; Wolock, D.M.; Meador, M.R.; Norris, R.H.

    2009-01-01

    Understanding the extent to which natural streamflow characteristics have been altered is an important consideration for ecological assessments of streams. Assessing hydrologic condition requires that we quantify the attributes of the flow regime that would be expected in the absence of anthropogenic modifications. The objective of this study was to evaluate whether selected streamflow characteristics could be predicted at regional and national scales using geospatial data. Long-term, gaged river basins distributed throughout the contiguous US that had streamflow characteristics representing least disturbed or near pristine conditions were identified. Thirteen metrics of the magnitude, frequency, duration, timing and rate of change of streamflow were calculated using a 20-50 year period of record for each site. We used random forests (RF), a robust statistical modelling approach, to develop models that predicted the value for each streamflow metric using natural watershed characteristics. We compared the performance (i.e. bias and precision) of national- and regional-scale predictive models to that of models based on landscape classifications, including major river basins, ecoregions and hydrologic landscape regions (HLR). For all hydrologic metrics, landscape stratification models produced estimates that were less biased and more precise than a null model that accounted for no natural variability. Predictive models at the national and regional scale performed equally well, and substantially improved predictions of all hydrologic metrics relative to landscape stratification models. Prediction error rates ranged from 15 to 40%, but were 25% for most metrics. We selected three gaged, non-reference sites to illustrate how predictive models could be used to assess hydrologic condition. These examples show how the models accurately estimate predisturbance conditions and are sensitive to changes in streamflow variability associated with long-term land-use change. We also

  19. Genetics

    International Nuclear Information System (INIS)

    Hubitschek, H.E.

    1975-01-01

    Progress is reported on the following research projects: genetic effects of high LET radiations; genetic regulation, alteration, and repair; chromosome replication and the division cycle of Escherichia coli; effects of radioisotope decay in the DNA of microorganisms; initiation and termination of DNA replication in Bacillus subtilis; mutagenesis in mouse myeloma cells; lethal and mutagenic effects of near-uv radiation; effect of 8-methoxypsoralen on photodynamic lethality and mutagenicity in Escherichia coli; DNA repair of the lethal effects of far-uv; and near uv irradiation of bacterial cells

  20. Genetic deletion of Mst1 alters T cell function and protects against autoimmunity.

    Directory of Open Access Journals (Sweden)

    Konstantin V Salojin

    Full Text Available Mammalian sterile 20-like kinase 1 (Mst1 is a MAPK kinase kinase kinase which is involved in a wide range of cellular responses, including apoptosis, lymphocyte adhesion and trafficking. The contribution of Mst1 to Ag-specific immune responses and autoimmunity has not been well defined. In this study, we provide evidence for the essential role of Mst1 in T cell differentiation and autoimmunity, using both genetic and pharmacologic approaches. Absence of Mst1 in mice reduced T cell proliferation and IL-2 production in vitro, blocked cell cycle progression, and elevated activation-induced cell death in Th1 cells. Mst1 deficiency led to a CD4+ T cell development path that was biased toward Th2 and immunoregulatory cytokine production with suppressed Th1 responses. In addition, Mst1-/- B cells showed decreased stimulation to B cell mitogens in vitro and deficient Ag-specific Ig production in vivo. Consistent with altered lymphocyte function, deletion of Mst1 reduced the severity of experimental autoimmune encephalomyelitis (EAE and protected against collagen-induced arthritis development. Mst1-/- CD4+ T cells displayed an intrinsic defect in their ability to respond to encephalitogenic antigens and deletion of Mst1 in the CD4+ T cell compartment was sufficient to alleviate CNS inflammation during EAE. These findings have prompted the discovery of novel compounds that are potent inhibitors of Mst1 and exhibit desirable pharmacokinetic properties. In conclusion, this report implicates Mst1 as a critical regulator of adaptive immune responses, Th1/Th2-dependent cytokine production, and as a potential therapeutic target for immune disorders.

  1. Genetic relatedness does not predict the queen's successors in the ...

    Indian Academy of Sciences (India)

    SAIKAT CHAKRABORTY

    2018-06-06

    Jun 6, 2018 ... 1Centre for Ecological Sciences, Indian Institute of Science, ... Ropalidia marginata is a social wasp in which colonies consist of a single .... Materials and methods .... Descriptive statistics about the genetic data were estimated.

  2. Increasing Prediction the Original Final Year Project of Student Using Genetic Algorithm

    Science.gov (United States)

    Saragih, Rijois Iboy Erwin; Turnip, Mardi; Sitanggang, Delima; Aritonang, Mendarissan; Harianja, Eva

    2018-04-01

    Final year project is very important forgraduation study of a student. Unfortunately, many students are not seriouslydidtheir final projects. Many of studentsask for someone to do it for them. In this paper, an application of genetic algorithms to predict the original final year project of a studentis proposed. In the simulation, the data of the final project for the last 5 years is collected. The genetic algorithm has several operators namely population, selection, crossover, and mutation. The result suggest that genetic algorithm can do better prediction than other comparable model. Experimental results of predicting showed that 70% was more accurate than the previous researched.

  3. Accounting for genetic architecture improves sequence based genomic prediction for a Drosophila fitness trait.

    Science.gov (United States)

    Ober, Ulrike; Huang, Wen; Magwire, Michael; Schlather, Martin; Simianer, Henner; Mackay, Trudy F C

    2015-01-01

    The ability to predict quantitative trait phenotypes from molecular polymorphism data will revolutionize evolutionary biology, medicine and human biology, and animal and plant breeding. Efforts to map quantitative trait loci have yielded novel insights into the biology of quantitative traits, but the combination of individually significant quantitative trait loci typically has low predictive ability. Utilizing all segregating variants can give good predictive ability in plant and animal breeding populations, but gives little insight into trait biology. Here, we used the Drosophila Genetic Reference Panel to perform both a genome wide association analysis and genomic prediction for the fitness-related trait chill coma recovery time. We found substantial total genetic variation for chill coma recovery time, with a genetic architecture that differs between males and females, a small number of molecular variants with large main effects, and evidence for epistasis. Although the top additive variants explained 36% (17%) of the genetic variance among lines in females (males), the predictive ability using genomic best linear unbiased prediction and a relationship matrix using all common segregating variants was very low for females and zero for males. We hypothesized that the low predictive ability was due to the mismatch between the infinitesimal genetic architecture assumed by the genomic best linear unbiased prediction model and the true genetic architecture of chill coma recovery time. Indeed, we found that the predictive ability of the genomic best linear unbiased prediction model is markedly improved when we combine quantitative trait locus mapping with genomic prediction by only including the top variants associated with main and epistatic effects in the relationship matrix. This trait-associated prediction approach has the advantage that it yields biologically interpretable prediction models.

  4. Accounting for genetic architecture improves sequence based genomic prediction for a Drosophila fitness trait.

    Directory of Open Access Journals (Sweden)

    Ulrike Ober

    Full Text Available The ability to predict quantitative trait phenotypes from molecular polymorphism data will revolutionize evolutionary biology, medicine and human biology, and animal and plant breeding. Efforts to map quantitative trait loci have yielded novel insights into the biology of quantitative traits, but the combination of individually significant quantitative trait loci typically has low predictive ability. Utilizing all segregating variants can give good predictive ability in plant and animal breeding populations, but gives little insight into trait biology. Here, we used the Drosophila Genetic Reference Panel to perform both a genome wide association analysis and genomic prediction for the fitness-related trait chill coma recovery time. We found substantial total genetic variation for chill coma recovery time, with a genetic architecture that differs between males and females, a small number of molecular variants with large main effects, and evidence for epistasis. Although the top additive variants explained 36% (17% of the genetic variance among lines in females (males, the predictive ability using genomic best linear unbiased prediction and a relationship matrix using all common segregating variants was very low for females and zero for males. We hypothesized that the low predictive ability was due to the mismatch between the infinitesimal genetic architecture assumed by the genomic best linear unbiased prediction model and the true genetic architecture of chill coma recovery time. Indeed, we found that the predictive ability of the genomic best linear unbiased prediction model is markedly improved when we combine quantitative trait locus mapping with genomic prediction by only including the top variants associated with main and epistatic effects in the relationship matrix. This trait-associated prediction approach has the advantage that it yields biologically interpretable prediction models.

  5. Hereditary melanoma and predictive genetic testing: why not?

    Science.gov (United States)

    Riedijk, S R; de Snoo, F A; van Dijk, S; Bergman, W; van Haeringen, A; Silberg, S; van Elderen, T M T; Tibben, A

    2005-09-01

    Since p16-Leiden presymptomatic testing for hereditary melanoma has become available in the Netherlands, the benefits and risks of offering such testing are evaluated. The current paper investigated why the non-participants were reluctant to participate in genetic testing. Sixty six eligible individuals, who were knowledgeable about the test but had not participated in genetic testing by January 2003, completed a self-report questionnaire assessing motivation, anxiety, family dynamics, risk knowledge and causal attributions. Non-participants reported anxiety levels below clinical significance. A principal components analysis on reasons for non-participation distinguished two underlying motives: emotional and rational motivation. Rational motivation for non-participation was associated with more accurate risk knowledge, the inclination to preselect mutation carriers within the family and lower scores on anxiety. Emotional motivation for non-participation was associated with disease misperceptions, hesitation to communicate unfavourable test results within the family and higher scores on anxiety. Rational and emotional motivation for non-participation in the genetic test for hereditary melanoma was found. Emotionally motivated individuals may be reluctant to disseminate genetic risk information. Rationally motivated individuals were better informed than emotionally motivated individuals. It is suggested that a leaflet is added to the invitation letter to enhance informed decision-making about genetic testing.

  6. Social interactions predict genetic diversification: an experimental manipulation in shorebirds.

    Science.gov (United States)

    Cunningham, Charles; Parra, Jorge E; Coals, Lucy; Beltrán, Marcela; Zefania, Sama; Székely, Tamás

    2018-01-01

    Mating strategy and social behavior influence gene flow and hence affect levels of genetic differentiation and potentially speciation. Previous genetic analyses of closely related plovers Charadrius spp. found strikingly different population genetic structure in Madagascar: Kittlitz's plovers are spatially homogenous whereas white-fronted plovers have well segregated and geographically distinct populations. Here, we test the hypotheses that Kittlitz's plovers are spatially interconnected and have extensive social interactions that facilitate gene flow, whereas white-fronted plovers are spatially discrete and have limited social interactions. By experimentally removing mates from breeding pairs and observing the movements of mate-searching plovers in both species, we compare the spatial behavior of Kittlitz's and white-fronted plovers within a breeding season. The behavior of experimental birds was largely consistent with expectations: Kittlitz's plovers travelled further, sought new mates in larger areas, and interacted with more individuals than white-fronted plovers, however there was no difference in breeding dispersal. These results suggest that mating strategies, through spatial behavior and social interactions, are predictors of gene flow and thus genetic differentiation and speciation. Our study highlights the importance of using social behavior to understand gene flow. However, further work is needed to investigate the relative importance of social structure, as well as intra- and inter-season dispersal, in influencing the genetic structures of populations.

  7. Genetic and epigenetic alteration among three homoeologous genes of a class E MADS box gene in hexaploid wheat.

    Science.gov (United States)

    Shitsukawa, Naoki; Tahira, Chikako; Kassai, Ken-Ichiro; Hirabayashi, Chizuru; Shimizu, Tomoaki; Takumi, Shigeo; Mochida, Keiichi; Kawaura, Kanako; Ogihara, Yasunari; Murai, Koji

    2007-06-01

    Bread wheat (Triticum aestivum) is a hexaploid species with A, B, and D ancestral genomes. Most bread wheat genes are present in the genome as triplicated homoeologous genes (homoeologs) derived from the ancestral species. Here, we report that both genetic and epigenetic alterations have occurred in the homoeologs of a wheat class E MADS box gene. Two class E genes are identified in wheat, wheat SEPALLATA (WSEP) and wheat LEAFY HULL STERILE1 (WLHS1), which are homologs of Os MADS45 and Os MADS1 in rice (Oryza sativa), respectively. The three wheat homoeologs of WSEP showed similar genomic structures and expression profiles. By contrast, the three homoeologs of WLHS1 showed genetic and epigenetic alterations. The A genome WLHS1 homoeolog (WLHS1-A) had a structural alteration that contained a large novel sequence in place of the K domain sequence. A yeast two-hybrid analysis and a transgenic experiment indicated that the WLHS1-A protein had no apparent function. The B and D genome homoeologs, WLHS1-B and WLHS1-D, respectively, had an intact MADS box gene structure, but WLHS1-B was predominantly silenced by cytosine methylation. Consequently, of the three WLHS1 homoeologs, only WLHS1-D functions in hexaploid wheat. This is a situation where three homoeologs are differentially regulated by genetic and epigenetic mechanisms.

  8. Linking neocortical, cognitive, and genetic variability in autism with alterations of brain plasticity: the Trigger-Threshold-Target model.

    Science.gov (United States)

    Mottron, Laurent; Belleville, Sylvie; Rouleau, Guy A; Collignon, Olivier

    2014-11-01

    The phenotype of autism involves heterogeneous adaptive traits (strengths vs. disabilities), different domains of alterations (social vs. non-social), and various associated genetic conditions (syndromic vs. nonsyndromic autism). Three observations suggest that alterations in experience-dependent plasticity are an etiological factor in autism: (1) the main cognitive domains enhanced in autism are controlled by the most plastic cortical brain regions, the multimodal association cortices; (2) autism and sensory deprivation share several features of cortical and functional reorganization; and (3) genetic mutations and/or environmental insults involved in autism all appear to affect developmental synaptic plasticity, and mostly lead to its upregulation. We present the Trigger-Threshold-Target (TTT) model of autism to organize these findings. In this model, genetic mutations trigger brain reorganization in individuals with a low plasticity threshold, mostly within regions sensitive to cortical reallocations. These changes account for the cognitive enhancements and reduced social expertise associated with autism. Enhanced but normal plasticity may underlie non-syndromic autism, whereas syndromic autism may occur when a triggering mutation or event produces an altered plastic reaction, also resulting in intellectual disability and dysmorphism in addition to autism. Differences in the target of brain reorganization (perceptual vs. language regions) account for the main autistic subgroups. In light of this model, future research should investigate how individual and sex-related differences in synaptic/regional brain plasticity influence the occurrence of autism. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

  9. Hopefulness predicts resilience after hereditary colorectal cancer genetic testing: a prospective outcome trajectories study

    OpenAIRE

    Chu Annie TW; Bonanno George A; Ho Judy WC; Ho Samuel MY; Chan Emily MS

    2010-01-01

    Abstract Background - Genetic testing for hereditary colorectal cancer (HCRC) had significant psychological consequences for test recipients. This prospective longitudinal study investigated the factors that predict psychological resilience in adults undergoing genetic testing for HCRC. Methods - A longitudinal study was carried out from April 2003 to August 2006 on Hong Kong Chinese HCRC family members who were recruited and offered genetic testing by the Hereditary Gastrointestinal Cancer R...

  10. Family Conflict Interacts with Genetic Liability in Predicting Childhood and Adolescent Depression

    Science.gov (United States)

    Rice, Frances; Harold, Gordon T.; Shelton, Katherine H.; Thapar, Anita

    2006-01-01

    Objective: To test for gene-environment interaction with depressive symptoms and family conflict. Specifically, to first examine whether the influence of family conflict in predicting depressive symptoms is increased in individuals at genetic risk of depression. Second, to test whether the genetic component of variance in depressive symptoms…

  11. The current and future use of ridge regression for prediction in quantitative genetics

    OpenAIRE

    Vlaming, Ronald; Groenen, Patrick

    2015-01-01

    textabstractIn recent years, there has been a considerable amount of research on the use of regularization methods for inference and prediction in quantitative genetics. Such research mostly focuses on selection of markers and shrinkage of their effects. In this review paper, the use of ridge regression for prediction in quantitative genetics using single-nucleotide polymorphism data is discussed. In particular, we consider (i) the theoretical foundations of ridge regression, (ii) its link to...

  12. Genetic KCa3.1-deficiency produces locomotor hyperactivity and alterations in cerebral monoamine levels.

    Directory of Open Access Journals (Sweden)

    Kate Lykke Lambertsen

    Full Text Available The calmodulin/calcium-activated K(+ channel KCa3.1 is expressed in red and white blood cells, epithelia and endothelia, and possibly central and peripheral neurons. However, our knowledge about its contribution to neurological functions and behavior is incomplete. Here, we investigated whether genetic deficiency or pharmacological activation of KCa3.1 change behavior and cerebral monoamine levels in mice.In the open field test, KCa3.1-deficiency increased horizontal activity, as KCa3.1(-/- mice travelled longer distances (≈145% of KCa3.1(+/+ and at higher speed (≈1.5-fold of KCa3.1(+/+. Working memory in the Y-maze was reduced by KCa3.1-deficiency. Motor coordination on the rotarod and neuromuscular functions were unchanged. In KCa3.1(-/- mice, HPLC analysis revealed that turn-over rates of serotonin were reduced in frontal cortex, striatum and brain stem, while noradrenalin turn-over rates were increased in the frontal cortex. Dopamine turn-over rates were unaltered. Plasma catecholamine and corticosterone levels were unaltered. Intraperitoneal injections of 10 mg/kg of the KCa3.1/KCa2-activator SKA-31 reduced rearing and turning behavior in KCa3.1(+/+ but not in KCa3.1(-/- mice, while 30 mg/kg SKA-31 caused strong sedation in 50% of the animals of either genotypes. KCa3.1(-/- mice were hyperactive (≈+60% in their home cage and SKA-31-administration reduced nocturnal physical activity in KCa3.1(+/+ but not in KCa3.1(-/- mice.KCa3.1-deficiency causes locomotor hyperactivity and altered monoamine levels in selected brain regions, suggesting a so far unknown functional link of KCa3.1 channels to behavior and monoaminergic neurotransmission in mice. The tranquilizing effects of low-dose SKA-31 raise the possibility to use KCa3.1/KCa2 channels as novel pharmacological targets for the treatment of neuropsychiatric hyperactivity disorders.

  13. Habitat Predicts Levels of Genetic Admixture in Saccharomyces cerevisiae

    Directory of Open Access Journals (Sweden)

    Viranga Tilakaratna

    2017-09-01

    Full Text Available Genetic admixture can provide material for populations to adapt to local environments, and this process has played a crucial role in the domestication of plants and animals. The model yeast, Saccharomyces cerevisiae, has been domesticated multiple times for the production of wine, sake, beer, and bread, but the high rate of admixture between yeast lineages has so far been treated as a complication for population genomic analysis. Here, we make use of the low recombination rate at centromeres to investigate admixture in yeast using a classic Bayesian approach and a locus-by-locus phylogenetic approach. Using both approaches, we find that S. cerevisiae from stable oak woodland habitats are less likely to show recent genetic admixture compared with those isolated from transient habitats such as fruits, wine, or human infections. When woodland yeast strains do show recent genetic admixture, the degree of admixture is lower than in strains from other habitats. Furthermore, S. cerevisiae populations from oak woodlands are genetically isolated from each other, with only occasional migration between woodlands and local fruit habitats. Application of the phylogenetic approach suggests that there is a previously undetected population in North Africa that is the closest outgroup to the European S. cerevisiae, including the domesticated Wine population. Careful testing for admixture in S. cerevisiae leads to a better understanding of the underlying population structure of the species and will be important for understanding the selective processes underlying domestication in this economically important species.

  14. Habitat Predicts Levels of Genetic Admixture in Saccharomyces cerevisiae.

    Science.gov (United States)

    Tilakaratna, Viranga; Bensasson, Douda

    2017-09-07

    Genetic admixture can provide material for populations to adapt to local environments, and this process has played a crucial role in the domestication of plants and animals. The model yeast, Saccharomyces cerevisiae , has been domesticated multiple times for the production of wine, sake, beer, and bread, but the high rate of admixture between yeast lineages has so far been treated as a complication for population genomic analysis. Here, we make use of the low recombination rate at centromeres to investigate admixture in yeast using a classic Bayesian approach and a locus-by-locus phylogenetic approach. Using both approaches, we find that S. cerevisiae from stable oak woodland habitats are less likely to show recent genetic admixture compared with those isolated from transient habitats such as fruits, wine, or human infections. When woodland yeast strains do show recent genetic admixture, the degree of admixture is lower than in strains from other habitats. Furthermore, S. cerevisiae populations from oak woodlands are genetically isolated from each other, with only occasional migration between woodlands and local fruit habitats. Application of the phylogenetic approach suggests that there is a previously undetected population in North Africa that is the closest outgroup to the European S. cerevisiae , including the domesticated Wine population. Careful testing for admixture in S. cerevisiae leads to a better understanding of the underlying population structure of the species and will be important for understanding the selective processes underlying domestication in this economically important species. Copyright © 2017 Tilakaratna and Bensasson.

  15. Genetic markers for prediction of normal tissue toxicity after radiotherapy

    DEFF Research Database (Denmark)

    Alsner, Jan; Andreassen, Christian Nicolaj; Overgaard, Jens

    2008-01-01

    During the last decade, a number of studies have supported the hypothesis that there is an important genetic component to the observed interpatient variability in normal tissue toxicity after radiotherapy. This review summarizes the candidate gene association studies published so far on the risk...

  16. Predictive genetic testing for cardiovascular diseases: Impact on carrier children

    NARCIS (Netherlands)

    Meulenkamp, Tineke M.; Tibben, Aad; Mollema, Eline D.; Van Langen, Irene M.; Wiegman, Albert; De Wert, Guido M.; De Beaufort, Inez D.; Wilde, Arthur A. M.; Smets, Ellen M. A.

    2008-01-01

    We studied the experiences of children identified by family screening who were found to be a mutation carrier for a genetic cardiovascular disease (Long QT Syndrome (LQTS), Hypertrophic Cardiomyopathy (HCM), Familial Hypercholesterolemia (FH)). We addressed the (a) manner in which they perceive

  17. Genetically Predicted Body Mass Index and Breast Cancer Risk

    DEFF Research Database (Denmark)

    Guo, Yan; Warren Andersen, Shaneda; Shu, Xiao-Ou

    2016-01-01

    BACKGROUND: Observational epidemiological studies have shown that high body mass index (BMI) is associated with a reduced risk of breast cancer in premenopausal women but an increased risk in postmenopausal women. It is unclear whether this association is mediated through shared genetic or enviro...

  18. Macro-environment of breast carcinoma: frequent genetic alterations in the normal appearing skins of patients with breast cancer.

    Science.gov (United States)

    Moinfar, Farid; Beham, Alfred; Friedrich, Gerhard; Deutsch, Alexander; Hrzenjak, Andelko; Luschin, Gero; Tavassoli, Fattaneh A

    2008-05-01

    Genetic abnormalities in microenvironmental tissues with subsequent alterations of reciprocal interactions between epithelial and mesenchymal cells play a key role in the breast carcinogenesis. Although a few reports have demonstrated abnormal fibroblastic functions in normal-appearing fibroblasts taken from the skins of breast cancer patients, the genetic basis of this phenomenon and its implication for carcinogenesis are unexplored. We analyzed 12 mastectomy specimens showing invasive ductal carcinomas. In each case, morphologically normal epidermis and dermis, carcinoma, normal stroma close to carcinoma, and stroma at a distant from carcinoma were microdissected. Metastatic-free lymphatic tissues from lymph nodes served as a control. Using PCR, DNA extracts were examined with 11 microsatellite markers known for a high frequency of allelic imbalances in breast cancer. Losses of heterozygosity and/or microsatellite instability were detected in 83% of the skin samples occurring either concurrently with or independently from the cancerous tissues. In 80% of these cases at least one microsatellite marker displayed loss of heterozygosity or microsatellite instability in the skin, which was absent in carcinoma. A total of 41% of samples showed alterations of certain loci observed exclusively in the carcinoma but not in the skin compartments. Our study suggests that breast cancer is not just a localized genetic disorder, but rather part of a larger field of genetic alterations/instabilities affecting multiple cell populations in the organ with various cellular elements, ultimately contributing to the manifestation of the more 'localized' carcinoma. These data indicate that more global assessment of tumor micro- and macro-environment is crucial for our understanding of breast carcinogenesis.

  19. Estimation of genetic connectedness diagnostics based on prediction errors without the prediction error variance-covariance matrix.

    Science.gov (United States)

    Holmes, John B; Dodds, Ken G; Lee, Michael A

    2017-03-02

    An important issue in genetic evaluation is the comparability of random effects (breeding values), particularly between pairs of animals in different contemporary groups. This is usually referred to as genetic connectedness. While various measures of connectedness have been proposed in the literature, there is general agreement that the most appropriate measure is some function of the prediction error variance-covariance matrix. However, obtaining the prediction error variance-covariance matrix is computationally demanding for large-scale genetic evaluations. Many alternative statistics have been proposed that avoid the computational cost of obtaining the prediction error variance-covariance matrix, such as counts of genetic links between contemporary groups, gene flow matrices, and functions of the variance-covariance matrix of estimated contemporary group fixed effects. In this paper, we show that a correction to the variance-covariance matrix of estimated contemporary group fixed effects will produce the exact prediction error variance-covariance matrix averaged by contemporary group for univariate models in the presence of single or multiple fixed effects and one random effect. We demonstrate the correction for a series of models and show that approximations to the prediction error matrix based solely on the variance-covariance matrix of estimated contemporary group fixed effects are inappropriate in certain circumstances. Our method allows for the calculation of a connectedness measure based on the prediction error variance-covariance matrix by calculating only the variance-covariance matrix of estimated fixed effects. Since the number of fixed effects in genetic evaluation is usually orders of magnitudes smaller than the number of random effect levels, the computational requirements for our method should be reduced.

  20. Genetic fuzzy system predicting contractile reactivity patterns of small arteries

    DEFF Research Database (Denmark)

    Tang, J; Sheykhzade, Majid; Clausen, B F

    2014-01-01

    strategies. Results show that optimized fuzzy systems (OFSs) predict contractile reactivity of arteries accurately. In addition, OFSs identified significant differences that were undetectable using conventional analysis in the responses of arteries between groups. We concluded that OFSs may be used...

  1. The potential of large studies for building genetic risk prediction models

    Science.gov (United States)

    NCI scientists have developed a new paradigm to assess hereditary risk prediction in common diseases, such as prostate cancer. This genetic risk prediction concept is based on polygenic analysis—the study of a group of common DNA sequences, known as singl

  2. Prediction of quantitative phenotypes based on genetic networks: a case study in yeast sporulation

    Directory of Open Access Journals (Sweden)

    Shen Li

    2010-09-01

    Full Text Available Abstract Background An exciting application of genetic network is to predict phenotypic consequences for environmental cues or genetic perturbations. However, de novo prediction for quantitative phenotypes based on network topology is always a challenging task. Results Using yeast sporulation as a model system, we have assembled a genetic network from literature and exploited Boolean network to predict sporulation efficiency change upon deleting individual genes. We observe that predictions based on the curated network correlate well with the experimentally measured values. In addition, computational analysis reveals the robustness and hysteresis of the yeast sporulation network and uncovers several patterns of sporulation efficiency change caused by double gene deletion. These discoveries may guide future investigation of underlying mechanisms. We have also shown that a hybridized genetic network reconstructed from both temporal microarray data and literature is able to achieve a satisfactory prediction accuracy of the same quantitative phenotypes. Conclusions This case study illustrates the value of predicting quantitative phenotypes based on genetic network and provides a generic approach.

  3. Integrating environmental and genetic effects to predict responses of tree populations to climate.

    Science.gov (United States)

    Wang, Tongli; O'Neill, Gregory A; Aitken, Sally N

    2010-01-01

    Climate is a major environmental factor affecting the phenotype of trees and is also a critical agent of natural selection that has molded among-population genetic variation. Population response functions describe the environmental effect of planting site climates on the performance of a single population, whereas transfer functions describe among-population genetic variation molded by natural selection for climate. Although these approaches are widely used to predict the responses of trees to climate change, both have limitations. We present a novel approach that integrates both genetic and environmental effects into a single "universal response function" (URF) to better predict the influence of climate on phenotypes. Using a large lodgepole pine (Pinus contorta Dougl. ex Loud.) field transplant experiment composed of 140 populations planted on 62 sites to demonstrate the methodology, we show that the URF makes full use of data from provenance trials to: (1) improve predictions of climate change impacts on phenotypes; (2) reduce the size and cost of future provenance trials without compromising predictive power; (3) more fully exploit existing, less comprehensive provenance tests; (4) quantify and compare environmental and genetic effects of climate on population performance; and (5) predict the performance of any population growing in any climate. Finally, we discuss how the last attribute allows the URF to be used as a mechanistic model to predict population and species ranges for the future and to guide assisted migration of seed for reforestation, restoration, or afforestation and genetic conservation in a changing climate.

  4. Revealing life-history traits by contrasting genetic estimations with predictions of effective population size.

    Science.gov (United States)

    Greenbaum, Gili; Renan, Sharon; Templeton, Alan R; Bouskila, Amos; Saltz, David; Rubenstein, Daniel I; Bar-David, Shirli

    2017-12-22

    Effective population size, a central concept in conservation biology, is now routinely estimated from genetic surveys and can also be theoretically predicted from demographic, life-history, and mating-system data. By evaluating the consistency of theoretical predictions with empirically estimated effective size, insights can be gained regarding life-history characteristics and the relative impact of different life-history traits on genetic drift. These insights can be used to design and inform management strategies aimed at increasing effective population size. We demonstrated this approach by addressing the conservation of a reintroduced population of Asiatic wild ass (Equus hemionus). We estimated the variance effective size (N ev ) from genetic data (N ev =24.3) and formulated predictions for the impacts on N ev of demography, polygyny, female variance in lifetime reproductive success (RS), and heritability of female RS. By contrasting the genetic estimation with theoretical predictions, we found that polygyny was the strongest factor affecting genetic drift because only when accounting for polygyny were predictions consistent with the genetically measured N ev . The comparison of effective-size estimation and predictions indicated that 10.6% of the males mated per generation when heritability of female RS was unaccounted for (polygyny responsible for 81% decrease in N ev ) and 19.5% mated when female RS was accounted for (polygyny responsible for 67% decrease in N ev ). Heritability of female RS also affected N ev ; hf2=0.91 (heritability responsible for 41% decrease in N ev ). The low effective size is of concern, and we suggest that management actions focus on factors identified as strongly affecting Nev, namely, increasing the availability of artificial water sources to increase number of dominant males contributing to the gene pool. This approach, evaluating life-history hypotheses in light of their impact on effective population size, and contrasting

  5. Stream Flow Prediction by Remote Sensing and Genetic Programming

    Science.gov (United States)

    Chang, Ni-Bin

    2009-01-01

    A genetic programming (GP)-based, nonlinear modeling structure relates soil moisture with synthetic-aperture-radar (SAR) images to present representative soil moisture estimates at the watershed scale. Surface soil moisture measurement is difficult to obtain over a large area due to a variety of soil permeability values and soil textures. Point measurements can be used on a small-scale area, but it is impossible to acquire such information effectively in large-scale watersheds. This model exhibits the capacity to assimilate SAR images and relevant geoenvironmental parameters to measure soil moisture.

  6. Urinary Neurotransmitters Are Selectively Altered in Children With Obstructive Sleep Apnea and Predict Cognitive Morbidity

    Science.gov (United States)

    Kheirandish-Gozal, Leila; McManus, Corena J. T.; Kellermann, Gottfried H.; Samiei, Arash

    2013-01-01

    Background: Pediatric obstructive sleep apnea (OSA) is associated with cognitive dysfunction, suggesting altered neurotransmitter function. We explored overnight changes in neurotransmitters in the urine of children with and without OSA. Methods: Urine samples were collected from children with OSA and from control subjects before and after sleep studies. A neurocognitive battery assessing general cognitive ability (GCA) was administered to a subset of children with OSA. Samples were subjected to multiple enzyme-linked immunosorbent assays for 12 neurotransmitters, and adjusted for creatinine concentrations. Results: The study comprised 50 children with OSA and 20 control subjects. Of the children with OSA, 20 had normal GCA score (mean ± SD) (101.2 ± 14.5) and 16 had a reduced GCA score (87.3 ± 13.9; P neurotransmitters enabled prediction of OSA (area under the curve [AUC]: 0.923; P neurotransmitters in urine may not only predict OSA but also the presence of cognitive deficits. Larger cohort studies appear warranted to confirm these findings. PMID:23306904

  7. Global DNA methylation is altered by neoadjuvant chemoradiotherapy in rectal cancer and may predict response to treatment - A pilot study.

    LENUS (Irish Health Repository)

    Tsang, J S

    2014-07-28

    In rectal cancer, not all tumours display a response to neoadjuvant treatment. An accurate predictor of response does not exist to guide patient-specific treatment. DNA methylation is a distinctive molecular pathway in colorectal carcinogenesis. Whether DNA methylation is altered by neoadjuvant treatment and a potential response predictor is unknown. We aimed to determine whether DNA methylation is altered by neoadjuvant chemoradiotherapy (CRT) and to determine its role in predicting response to treatment.

  8. The genetic alteration of MTS1/CDKN2 gene in esophageal cancer

    International Nuclear Information System (INIS)

    Zo, Jae Ill; Paik, Hee Jong; Park, Jong Ho; Kim, Mi Hee

    1996-12-01

    MTS1/CDKN2 gene plays a key role in cell cycle regulation, and there have been many studies about the significance of this gene in tumorigenesis. To investigate the frequency of MTS1/CDKN2 gene alteration in Korean esophageal cancer, we studied 36 esophageal cancer tissues with paired PCR analysis to detect homozygous deletion and PCR-SSCP methods to find minute mutations, if any. In the cases with abnormalities, the nucleotide sequence analysis was performed. And in cases without RB gene a alterations, direct sequence analysis was also done. There was no homozygous deletions. Mobility shift by PCR-SSCP was observed in four cases at exon 2, which showed 1 bp deletion in codon 97 of mutation in codon 100 which changed TAT (Tyr) from GAT (Asp). But there were not MTS1/CDKN2 gene alterations in cases without Rb gene alterations. Analysis of clinical data did not show any differences depending upon MTS1/CDKN2 gene alterations. Therefore the MTS1/CDKN2 gene mutations were infrequent events and do not play a major role in the group of patients examined. More study for contribution of methylation in MTS1/CDKN2 gene for inactivation of p16 should be done before evaluation and application of MTS1/CDKN2 gene in tumorigenesis and as an candidate of gene therapy. (author). 15 refs

  9. The genetic alteration of MTS1/CDKN2 gene in esophageal cancer

    Energy Technology Data Exchange (ETDEWEB)

    Zo, Jae Ill; Paik, Hee Jong; Park, Jong Ho; Kim, Mi Hee [Korea Cancer Center Hospital, Seoul (Korea, Republic of)

    1996-12-01

    MTS1/CDKN2 gene plays a key role in cell cycle regulation, and there have been many studies about the significance of this gene in tumorigenesis. To investigate the frequency of MTS1/CDKN2 gene alteration in Korean esophageal cancer, we studied 36 esophageal cancer tissues with paired PCR analysis to detect homozygous deletion and PCR-SSCP methods to find minute mutations, if any. In the cases with abnormalities, the nucleotide sequence analysis was performed. And in cases without RB gene a alterations, direct sequence analysis was also done. There was no homozygous deletions. Mobility shift by PCR-SSCP was observed in four cases at exon 2, which showed 1 bp deletion in codon 97 of mutation in codon 100 which changed TAT (Tyr) from GAT (Asp). But there were not MTS1/CDKN2 gene alterations in cases without Rb gene alterations. Analysis of clinical data did not show any differences depending upon MTS1/CDKN2 gene alterations. Therefore the MTS1/CDKN2 gene mutations were infrequent events and do not play a major role in the group of patients examined. More study for contribution of methylation in MTS1/CDKN2 gene for inactivation of p16 should be done before evaluation and application of MTS1/CDKN2 gene in tumorigenesis and as an candidate of gene therapy. (author). 15 refs.

  10. Estimating Additive and Non-Additive Genetic Variances and Predicting Genetic Merits Using Genome-Wide Dense Single Nucleotide Polymorphism Markers

    DEFF Research Database (Denmark)

    Su, Guosheng; Christensen, Ole Fredslund; Ostersen, Tage

    2012-01-01

    of genomic predictions for daily gain in pigs. In the analysis of daily gain, four linear models were used: 1) a simple additive genetic model (MA), 2) a model including both additive and additive by additive epistatic genetic effects (MAE), 3) a model including both additive and dominance genetic effects...

  11. Genetic Variation in Choline-Metabolizing Enzymes Alters Choline Metabolism in Young Women Consuming Choline Intakes Meeting Current Recommendations

    Directory of Open Access Journals (Sweden)

    Ariel B. Ganz

    2017-01-01

    Full Text Available Single nucleotide polymorphisms (SNPs in choline metabolizing genes are associated with disease risk and greater susceptibility to organ dysfunction under conditions of dietary choline restriction. However, the underlying metabolic signatures of these variants are not well characterized and it is unknown whether genotypic differences persist at recommended choline intakes. Thus, we sought to determine if common genetic risk factors alter choline dynamics in pregnant, lactating, and non-pregnant women consuming choline intakes meeting and exceeding current recommendations. Women (n = 75 consumed 480 or 930 mg choline/day (22% as a metabolic tracer, choline-d9 for 10–12 weeks in a controlled feeding study. Genotyping was performed for eight variant SNPs and genetic differences in metabolic flux and partitioning of plasma choline metabolites were evaluated using stable isotope methodology. CHKA rs10791957, CHDH rs9001, CHDH rs12676, PEMT rs4646343, PEMT rs7946, FMO3 rs2266782, SLC44A1 rs7873937, and SLC44A1 rs3199966 altered the use of choline as a methyl donor; CHDH rs9001 and BHMT rs3733890 altered the partitioning of dietary choline between betaine and phosphatidylcholine synthesis via the cytidine diphosphate (CDP-choline pathway; and CHKA rs10791957, CHDH rs12676, PEMT rs4646343, PEMT rs7946 and SLC44A1 rs7873937 altered the distribution of dietary choline between the CDP-choline and phosphatidylethanolamine N-methyltransferase (PEMT denovo pathway. Such metabolic differences may contribute to disease pathogenesis and prognosis over the long-term.

  12. Adaboost Ensemble with Simple Genetic Algorithm for Student Prediction Mode

    OpenAIRE

    AhmedSharaf ElDen; ElDen1Malaka A. Moustafa2Hany; M. Harb; AbdelH.Emara

    2013-01-01

    Predicting the student performance is a great concern to the higher education managements.Thisprediction helps to identify and to improve students' performance.Several factors may improve thisperformance.In the present study, we employ the data mining processes, particularly classification, toenhance the quality of the higher educational system. Recently, a new direction is used for the improvementof the classification accuracy by combining classifiers.In thispaper, we design and evaluate a f...

  13. Y chromosome microdeletions and alterations of spermatogenesis, patient approach and genetic counseling.

    Science.gov (United States)

    Rives, Nathalie

    2014-05-01

    Infertility affects 15% of couples at reproductive age and human male infertility appears frequently idiopathic. The main genetic causes of spermatogenesis defect responsible for non-obstructive azoospermia and severe oligozoospermia are constitutional chromosomal abnormalities and microdeletions in the azoospermia factor region of the Y chromosome. The improvement of the Yq microdeletion screening method gave new insights in the mechanism responsible for the genesis of Yq microdeletions and for the consequences of the management of male infertility and genetic counselling in case of assisted reproductive technology. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

  14. Prognostic and predictive value of VHL gene alteration in renal cell carcinoma: a meta-analysis and review.

    Science.gov (United States)

    Kim, Bum Jun; Kim, Jung Han; Kim, Hyeong Su; Zang, Dae Young

    2017-02-21

    The von Hippel-Lindau (VHL) gene is often inactivated in sporadic renal cell carcinoma (RCC) by mutation or promoter hypermethylation. The prognostic or predictive value of VHL gene alteration is not well established. We conducted this meta-analysis to evaluate the association between the VHL alteration and clinical outcomes in patients with RCC. We searched PUBMED, MEDLINE and EMBASE for articles including following terms in their titles, abstracts, or keywords: 'kidney or renal', 'carcinoma or cancer or neoplasm or malignancy', 'von Hippel-Lindau or VHL', 'alteration or mutation or methylation', and 'prognostic or predictive'. There were six studies fulfilling inclusion criteria and a total of 633 patients with clear cell RCC were included in the study: 244 patients who received anti-vascular endothelial growth factor (VEGF) therapy in the predictive value analysis and 419 in the prognostic value analysis. Out of 663 patients, 410 (61.8%) had VHL alteration. The meta-analysis showed no association between the VHL gene alteration and overall response rate (relative risk = 1.47 [95% CI, 0.81-2.67], P = 0.20) or progression free survival (hazard ratio = 1.02 [95% CI, 0.72-1.44], P = 0.91) in patients with RCC who received VEGF-targeted therapy. There was also no correlation between the VHL alteration and overall survival (HR = 0.80 [95% CI, 0.56-1.14], P = 0.21). In conclusion, this meta-analysis indicates that VHL gene alteration has no prognostic or predictive value in patients with clear cell RCC.

  15. Temporal organization of feeding in Syrian hamsters with a genetically altered circadian period

    NARCIS (Netherlands)

    Oklejewicz, M; Overkamp, GJF; Stirland, JA; Daan, S

    2001-01-01

    The variation in spontaneous meal patterning was studied in three genotypes (tau +/+, tau +/- and tau -/-) of the Syrian hamster with an altered circadian period. Feeding activity was monitored continuously in 13 individuals from each genotype in constant dim light conditions. All three genotypes

  16. Anthropogenic fragmentation may not alter pre-existing patterns of genetic diversity and differentiation in perennial shrubs.

    Science.gov (United States)

    Llorens, Tanya M; Ayre, David J; Whelan, Robert J

    2018-04-01

    Many plant species have pollination and seed dispersal systems and evolutionary histories that have produced strong genetic structuring. These genetic patterns may be consistent with expectations following recent anthropogenic fragmentation, making it difficult to detect fragmentation effects if no prefragmentation genetic data are available. We used microsatellite markers to investigate whether severe habitat fragmentation may have affected the structure and diversity of populations of the endangered Australian bird-pollinated shrub Grevillea caleyi R.Br., by comparing current patterns of genetic structure and diversity with those of the closely related G. longifolia R.Br. that has a similar life history but has not experienced anthropogenic fragmentation. Grevillea caleyi and G. longifolia showed similar and substantial population subdivision at all spatial levels (global F' ST  = 0.615 and 0.454; S p  = 0.039 and 0.066), marked isolation by distance and large heterozygous deficiencies. These characteristics suggest long-term effects of inbreeding in self-compatible species that have poor seed dispersal, limited connectivity via pollen flow and undergo population bottlenecks because of periodic fires. Highly structured allele size distributions, most notably in G. caleyi, imply historical processes of drift and mutation were important in isolated subpopulations. Genetic diversity did not vary with population size but was lower in more isolated populations for both species. Through this comparison, we reject the hypothesis that anthropogenic fragmentation has impacted substantially on the genetic composition or structure of G. caleyi populations. Our results suggest that highly self-compatible species with limited dispersal may be relatively resilient to the genetic changes predicted to follow habitat fragmentation. © 2018 John Wiley & Sons Ltd.

  17. Genetic KCa3.1-deficiency produces locomotor hyperactivity and alterations in cerebral monoamine levels

    DEFF Research Database (Denmark)

    Lambertsen, Kate Lykke; Gramsbergen, Jan Bert; Sivasaravanaparan, Mithula

    2012-01-01

    The calmodulin/calcium-activated K(+) channel KCa3.1 is expressed in red and white blood cells, epithelia and endothelia, and possibly central and peripheral neurons. However, our knowledge about its contribution to neurological functions and behavior is incomplete. Here, we investigated whether...... genetic deficiency or pharmacological activation of KCa3.1 change behavior and cerebral monoamine levels in mice....

  18. [Analysis of 14 individuals who requested predictive genetic testing for hereditary neuromuscular diseases].

    Science.gov (United States)

    Yoshida, Kunihiro; Tamai, Mariko; Kubota, Takeo; Kawame, Hiroshi; Amano, Naoji; Ikeda, Shu-ichi; Fukushima, Yoshimitsu

    2002-02-01

    Predictive genetic testing for hereditary neuromuscular diseases is a delicate issue for individuals at risk and their families, as well as for medical staff because these diseases are often late-onset and intractable. Therefore careful pre- and post-test genetic counseling and psychosocial support should be provided along with such genetic testing. The Division of Clinical and Molecular Genetics was established at our hospital in May 1996 to provide skilled professional genetic counseling. Since its establishment, 14 individuals have visited our clinic to request predictive genetic testing for hereditary neuromuscular diseases (4 for myotonic dystrophy, 6 for spinocerebellar ataxia, 3 for Huntington's disease, and 1 for Alzheimer's disease). The main reasons for considering testing were to remove uncertainty about the genetic status and to plan for the future. Nine of 14 individuals requested testing for making decisions about a forthcoming marriage or pregnancy (family planning). Other reasons raised by the individuals included career or financial planning, planning for their own health care, and knowing the risk for their children. At the first genetic counseling session, all of the individuals expressed hopes of not being a gene carrier and of escaping from fear of disease, and seemed not to be mentally well prepared for an increased-risk result. To date, 7 of the 14 individuals have received genetic testing and only one, who underwent predictive genetic testing for spinocerebellar ataxia, was given an increased-risk result. The seven individuals including the one with an increased-risk result, have coped well with their new knowledge about their genetic status after the testing results were disclosed. None of them has expressed regret. In pre-test genetic counseling sessions, we consider it quite important not only to determine the psychological status of the individual, but also to make the individual try to anticipate the changes in his/her life upon

  19. Altered protein glycosylation predicts Alzheimer's disease and modulates its pathology in disease model Drosophila.

    Science.gov (United States)

    Frenkel-Pinter, Moran; Stempler, Shiri; Tal-Mazaki, Sharon; Losev, Yelena; Singh-Anand, Avnika; Escobar-Álvarez, Daniela; Lezmy, Jonathan; Gazit, Ehud; Ruppin, Eytan; Segal, Daniel

    2017-08-01

    The pathological hallmarks of Alzheimer's disease (AD) are pathogenic oligomers and fibrils of misfolded amyloidogenic proteins (e.g., β-amyloid and hyper-phosphorylated tau in AD), which cause progressive loss of neurons in the brain and nervous system. Although deviations from normal protein glycosylation have been documented in AD, their role in disease pathology has been barely explored. Here our analysis of available expression data sets indicates that many glycosylation-related genes are differentially expressed in brains of AD patients compared with healthy controls. The robust differences found enabled us to predict the occurrence of AD with remarkable accuracy in a test cohort and identify a set of key genes whose expression determines this classification. We then studied in vivo the effect of reducing expression of homologs of 6 of these genes in transgenic Drosophila overexpressing human tau, a well-established invertebrate AD model. These experiments have led to the identification of glycosylation genes that may augment or ameliorate tauopathy phenotypes. Our results indicate that OstDelta, l(2)not and beta4GalT7 are tauopathy suppressors, whereas pgnat5 and CG33303 are enhancers, of tauopathy. These results suggest that specific alterations in protein glycosylation may play a causal role in AD etiology. Copyright © 2017 Elsevier Inc. All rights reserved.

  20. Altered neural reward and loss processing and prediction error signalling in depression

    Science.gov (United States)

    Ubl, Bettina; Kuehner, Christine; Kirsch, Peter; Ruttorf, Michaela

    2015-01-01

    Dysfunctional processing of reward and punishment may play an important role in depression. However, functional magnetic resonance imaging (fMRI) studies have shown heterogeneous results for reward processing in fronto-striatal regions. We examined neural responsivity associated with the processing of reward and loss during anticipation and receipt of incentives and related prediction error (PE) signalling in depressed individuals. Thirty medication-free depressed persons and 28 healthy controls performed an fMRI reward paradigm. Regions of interest analyses focused on neural responses during anticipation and receipt of gains and losses and related PE-signals. Additionally, we assessed the relationship between neural responsivity during gain/loss processing and hedonic capacity. When compared with healthy controls, depressed individuals showed reduced fronto-striatal activity during anticipation of gains and losses. The groups did not significantly differ in response to reward and loss outcomes. In depressed individuals, activity increases in the orbitofrontal cortex and nucleus accumbens during reward anticipation were associated with hedonic capacity. Depressed individuals showed an absence of reward-related PEs but encoded loss-related PEs in the ventral striatum. Depression seems to be linked to blunted responsivity in fronto-striatal regions associated with limited motivational responses for rewards and losses. Alterations in PE encoding might mirror blunted reward- and enhanced loss-related associative learning in depression. PMID:25567763

  1. Dynamics of ASXL1 mutation and other associated genetic alterations during disease progression in patients with primary myelodysplastic syndrome

    International Nuclear Information System (INIS)

    Chen, T-C; Hou, H-A; Chou, W-C; Tang, J-L; Kuo, Y-Y; Chen, C-Y; Tseng, M-H; Huang, C-F; Lai, Y-J; Chiang, Y-C; Lee, F-Y; Liu, M-C; Liu, C-W; Liu, C-Y; Yao, M; Huang, S-Y; Ko, B-S; Hsu, S-C; Wu, S-J; Tsay, W; Chen, Y-C; Tien, H-F

    2014-01-01

    Recently, mutations of the additional sex comb-like 1 (ASXL1) gene were identified in patients with myelodysplastic syndrome (MDS), but the interaction of this mutation with other genetic alterations and its dynamic changes during disease progression remain to be determined. In this study, ASXL1 mutations were identified in 106 (22.7%) of the 466 patients with primary MDS based on the French-American-British (FAB) classification and 62 (17.1%) of the 362 patients based on the World Health Organization (WHO) classification. ASXL1 mutation was closely associated with trisomy 8 and mutations of RUNX1, EZH2, IDH, NRAS, JAK2, SETBP1 and SRSF2, but was negatively associated with SF3B1 mutation. Most ASXL1-mutated patients (85%) had concurrent other gene mutations at diagnosis. ASXL1 mutation was an independent poor prognostic factor for survival. Sequential studies showed that the original ASXL1 mutation remained unchanged at disease progression in all 32 ASXL1-mutated patients but were frequently accompanied with acquisition of mutations of other genes, including RUNX1, NRAS, KRAS, SF3B1, SETBP1 and chromosomal evolution. On the other side, among the 80 ASXL1-wild patients, only one acquired ASXL1 mutation at leukemia transformation. In conclusion, ASXL1 mutations in association with other genetic alterations may have a role in the development of MDS but contribute little to disease progression

  2. Altering BDNF expression by genetics and/or environment: impact for emotional and depression-like behaviour in laboratory mice.

    Science.gov (United States)

    Chourbaji, Sabine; Brandwein, Christiane; Gass, Peter

    2011-01-01

    According to the "neurotrophin hypothesis", brain-derived neurotrophic factor (BDNF) is an important candidate gene in depression. Moreover, environmental stress is known to represent a risk factor in the pathophysiology and treatment of this disease. To elucidate, whether changes of BDNF availability signify cause or consequence of depressive-like alterations, it is essential to look for endophenotypes under distinct genetic conditions (e.g. altered BDNF expression). Furthermore it is crucial to examine environment-driven BDNF regulation and its effect on depressive-linked features. Consequently, gene × environment studies investigating prospective genetic mouse models of depression in different environmental contexts become increasingly important. The present review summarizes recent findings in BDNF-mutant mice, which have been controversially discussed as models of depression and anxiety. It furthermore illustrates the potential of environment to serve as naturalistic stressor with the potential to modulate the phenotype in wildtype and mutant mice. Moreover, environment may exert protective effects by regulating BDNF levels as attributed to "environmental enrichment". The effect of this beneficial condition will also be discussed with regard to probable "curative/therapeutic" approaches. Copyright © 2010 Elsevier Ltd. All rights reserved.

  3. Ethical dilemmas in genetic testing: examples from the Cuban program for predictive diagnosis of hereditary ataxias.

    Science.gov (United States)

    Mariño, Tania Cruz; Armiñán, Rubén Reynaldo; Cedeño, Humberto Jorge; Mesa, José Miguel Laffita; Zaldivar, Yanetza González; Rodríguez, Raúl Aguilera; Santos, Miguel Velázquez; Mederos, Luis Enrique Almaguer; Herrera, Milena Paneque; Pérez, Luis Velázquez

    2011-06-01

    Predictive testing protocols are intended to help patients affected with hereditary conditions understand their condition and make informed reproductive choices. However, predictive protocols may expose clinicians and patients to ethical dilemmas that interfere with genetic counseling and the decision making process. This paper describes ethical dilemmas in a series of five cases involving predictive testing for hereditary ataxias in Cuba. The examples herein present evidence of the deeply controversial situations faced by both individuals at risk and professionals in charge of these predictive studies, suggesting a need for expanded guidelines to address such complexities.

  4. Genetic Alterations within the DENND1A Gene in Patients with Polycystic Ovary Syndrome (PCOS)

    DEFF Research Database (Denmark)

    Eriksen, Mette B; Nielsen, Michael F B; Brusgaard, Klaus

    2013-01-01

    sequencing. SNP genotyping was tested by allelic discrimination in real-time PCR in the additional patients and controls. Sequencing of the DENND1A gene identified eight SNPs; seven were not known to be associated with any diseases. One missense SNP was detected (rs189947178, A/C), potentially altering......Polycystic ovary syndrome (PCOS), the most common endocrine disease among premenopausal women, is caused by both genes and environment. We and others previously reported association between single nucleotide polymorphisms (SNPs) in the DENND1A gene and PCOS. We therefore sequenced the DENND1A gene...... and FG-score or PCOS diagnosis, this could be a false positive finding. In conclusion, sequence analysis of the DENND1A gene of patients with PCOS did not identify alterations that alone could be responsible for the PCOS pathogenesis, but a missense SNP (rs189947178) was identified in one patient...

  5. Multiple genetic interaction experiments provide complementary information useful for gene function prediction.

    Directory of Open Access Journals (Sweden)

    Magali Michaut

    Full Text Available Genetic interactions help map biological processes and their functional relationships. A genetic interaction is defined as a deviation from the expected phenotype when combining multiple genetic mutations. In Saccharomyces cerevisiae, most genetic interactions are measured under a single phenotype - growth rate in standard laboratory conditions. Recently genetic interactions have been collected under different phenotypic readouts and experimental conditions. How different are these networks and what can we learn from their differences? We conducted a systematic analysis of quantitative genetic interaction networks in yeast performed under different experimental conditions. We find that networks obtained using different phenotypic readouts, in different conditions and from different laboratories overlap less than expected and provide significant unique information. To exploit this information, we develop a novel method to combine individual genetic interaction data sets and show that the resulting network improves gene function prediction performance, demonstrating that individual networks provide complementary information. Our results support the notion that using diverse phenotypic readouts and experimental conditions will substantially increase the amount of gene function information produced by genetic interaction screens.

  6. Flight initiation and maintenance deficits in flies with genetically altered biogenic amine levels

    OpenAIRE

    Brembs, Björn; Christiansen, F.; Pflüger, J.; Duch, C.

    2007-01-01

    Insect flight is one of the fastest, most intense and most energy-demanding motor behaviors. It is modulated on multiple levels by the biogenic amine octopamine. Within the CNS, octopamine acts directly on the flight central pattern generator, and it affects motivational states. In the periphery, octopamine sensitizes sensory receptors, alters muscle contraction kinetics, and enhances flight muscle glycolysis. This study addresses the roles for octopamine and its precursor tyramine in flight ...

  7. Quantitative Chemical-Genetic Interaction Map Connects Gene Alterations to Drug Responses | Office of Cancer Genomics

    Science.gov (United States)

    In a recent Cancer Discovery report, CTD2 researchers at the University of California in San Francisco developed a new quantitative chemical-genetic interaction mapping approach to evaluate drug sensitivity or resistance in isogenic cell lines. Performing a high-throughput screen with isogenic cell lines allowed the researchers to explore the impact of a panel of emerging and established drugs on cells overexpressing a single cancer-associated gene in isolation.

  8. Can current moisture responses predict soil CO2 efflux under altered precipitation regimes? A synthesis of manipulation experiments

    DEFF Research Database (Denmark)

    Vicca, S.; Bahn, M.; Estiarte, M.

    2014-01-01

    dependencies of SCE. Hence, the most justified answer to the question of whether current moisture responses of SCE can be extrapolated to predict SCE under altered precipitation regimes is 'no' - as based on the most reliable data sets available. We strongly recommend that future experiments focus more...

  9. [Environmental and genetic variables related with alterations in language acquisition in early childhood].

    Science.gov (United States)

    Moriano-Gutierrez, A; Colomer-Revuelta, J; Sanjuan, J; Carot-Sierra, J M

    2017-01-01

    A great deal of research has addressed problems in the correct acquisition of language, but with few overall conclusions. The reasons for this lie in the individual variability, the existence of different measures for assessing language and the fact that a complex network of genetic and environmental factors are involved in its development. To review the environmental and genetic variables that have been studied to date, in order to gain a better under-standing of the causes of specific language impairment and create new evidence that can help in the development of screening systems for the early detection of these disorders. The environmental variables related with poorer early child language development include male gender, low level of education of the mother, familial history of problems with language or psychiatric problems, perinatal problems and health problems in early childhood. Bilingualism seems to be a protective factor. Temperament and language are related. Within the genetic factors there are several specific genes associated with language, two of which have a greater influence on its physiological acquisition: FOXP2 and CNTNAP2. The other genes that are most related with specific language disorders are ATP2C2, CMIP, ROBO2, ZNF277 and NOP9. The key to comprehending the development of specific language disorders lies in reaching an understanding of the true role played by genes in the ontogenesis, in the regulation of the different developmental processes, and how this role is modulated by the environment.

  10. Partial genetic deletion of neuregulin 1 and adolescent stress interact to alter NMDA receptor binding in the medial prefrontal cortex

    Directory of Open Access Journals (Sweden)

    Tariq Waseem Chohan

    2014-09-01

    Full Text Available Schizophrenia is thought to arise due to a complex interaction between genetic and environmental factors during early neurodevelopment. We have recently shown that partial genetic deletion of the schizophrenia susceptibility gene neuregulin 1 (Nrg1 and adolescent stress interact to disturb sensorimotor gating, neuroendocrine activity and dendritic morphology in mice. Both stress and Nrg1 may have converging effects upon N-methyl-D-aspartate receptors (NMDARs which are implicated in the pathogenesis of schizophrenia, sensorimotor gating and dendritic spine plasticity. Using an identical repeated restraint stress paradigm to our previous study, here we determined NMDAR binding across various brain regions in adolescent Nrg1 heterozygous (HET and wild-type (WT mice using [3H] MK-801 autoradiography. Repeated restraint stress increased NMDAR binding in the ventral part of the lateral septum (LSV and the dentate gyrus (DG of the hippocampus irrespective of genotype. Partial genetic deletion of Nrg1 interacted with adolescent stress to promote an altered pattern of NMDAR binding in the infralimbic (IL subregion of the medial prefrontal cortex. In the IL, whilst stress tended to increase NMDAR binding in WT mice, it decreased binding in Nrg1 HET mice. However in the DG, stress selectively increased the expression of NMDAR binding in Nrg1 HET mice but not WT mice. These results demonstrate a Nrg1-stress interaction during adolescence on NMDAR binding in the medial prefrontal cortex.

  11. Direct-to-consumer genetic testing for predicting sports performance and talent identification: Consensus statement

    Science.gov (United States)

    Webborn, Nick; Williams, Alun; McNamee, Mike; Bouchard, Claude; Pitsiladis, Yannis; Ahmetov, Ildus; Ashley, Euan; Byrne, Nuala; Camporesi, Silvia; Collins, Malcolm; Dijkstra, Paul; Eynon, Nir; Fuku, Noriyuki; Garton, Fleur C; Hoppe, Nils; Holm, Søren; Kaye, Jane; Klissouras, Vassilis; Lucia, Alejandro; Maase, Kamiel; Moran, Colin; North, Kathryn N; Pigozzi, Fabio; Wang, Guan

    2015-01-01

    The general consensus among sport and exercise genetics researchers is that genetic tests have no role to play in talent identification or the individualised prescription of training to maximise performance. Despite the lack of evidence, recent years have witnessed the rise of an emerging market of direct-to-consumer marketing (DTC) tests that claim to be able to identify children's athletic talents. Targeted consumers include mainly coaches and parents. There is concern among the scientific community that the current level of knowledge is being misrepresented for commercial purposes. There remains a lack of universally accepted guidelines and legislation for DTC testing in relation to all forms of genetic testing and not just for talent identification. There is concern over the lack of clarity of information over which specific genes or variants are being tested and the almost universal lack of appropriate genetic counselling for the interpretation of the genetic data to consumers. Furthermore independent studies have identified issues relating to quality control by DTC laboratories with different results being reported from samples from the same individual. Consequently, in the current state of knowledge, no child or young athlete should be exposed to DTC genetic testing to define or alter training or for talent identification aimed at selecting gifted children or adolescents. Large scale collaborative projects, may help to develop a stronger scientific foundation on these issues in the future. PMID:26582191

  12. Genetic Variance Partitioning and Genome-Wide Prediction with Allele Dosage Information in Autotetraploid Potato.

    Science.gov (United States)

    Endelman, Jeffrey B; Carley, Cari A Schmitz; Bethke, Paul C; Coombs, Joseph J; Clough, Mark E; da Silva, Washington L; De Jong, Walter S; Douches, David S; Frederick, Curtis M; Haynes, Kathleen G; Holm, David G; Miller, J Creighton; Muñoz, Patricio R; Navarro, Felix M; Novy, Richard G; Palta, Jiwan P; Porter, Gregory A; Rak, Kyle T; Sathuvalli, Vidyasagar R; Thompson, Asunta L; Yencho, G Craig

    2018-05-01

    As one of the world's most important food crops, the potato ( Solanum tuberosum L.) has spurred innovation in autotetraploid genetics, including in the use of SNP arrays to determine allele dosage at thousands of markers. By combining genotype and pedigree information with phenotype data for economically important traits, the objectives of this study were to (1) partition the genetic variance into additive vs. nonadditive components, and (2) determine the accuracy of genome-wide prediction. Between 2012 and 2017, a training population of 571 clones was evaluated for total yield, specific gravity, and chip fry color. Genomic covariance matrices for additive ( G ), digenic dominant ( D ), and additive × additive epistatic ( G # G ) effects were calculated using 3895 markers, and the numerator relationship matrix ( A ) was calculated from a 13-generation pedigree. Based on model fit and prediction accuracy, mixed model analysis with G was superior to A for yield and fry color but not specific gravity. The amount of additive genetic variance captured by markers was 20% of the total genetic variance for specific gravity, compared to 45% for yield and fry color. Within the training population, including nonadditive effects improved accuracy and/or bias for all three traits when predicting total genotypic value. When six F 1 populations were used for validation, prediction accuracy ranged from 0.06 to 0.63 and was consistently lower (0.13 on average) without allele dosage information. We conclude that genome-wide prediction is feasible in potato and that it will improve selection for breeding value given the substantial amount of nonadditive genetic variance in elite germplasm. Copyright © 2018 by the Genetics Society of America.

  13. The Impact of Genetic and Non-Genetic Factors on Warfarin Dose Prediction in MENA Region: A Systematic Review.

    Science.gov (United States)

    Bader, Loulia Akram; Elewa, Hazem

    2016-01-01

    Warfarin is the most commonly used oral anticoagulant for the treatment and prevention of thromboembolic disorders. Pharmacogenomics studies have shown that variants in CYP2C9 and VKORC1 genes are strongly and consistently associated with warfarin dose variability. Although different populations from the Middle East and North Africa (MENA) region may share the same ancestry, it is still unclear how they compare in the genetic and non-genetic factors affecting their warfarin dosing. To explore the prevalence of CYP2C9 and VKORC1 variants in MENA, and the effect of these variants along with other non-genetic factors in predicting warfarin dose. In this systematic review, we included observational cross sectional and cohort studies that enrolled patients on stable warfarin dose and had the genetics and non-genetics factors associated with mean warfarin dose as the primary outcome. We searched PubMed, Medline, Scopus, PharmGKB, PHGKB, Google scholar and reference lists of relevant reviews. We identified 17 studies in eight different populations: Iranian, Israeli, Egyptian, Lebanese, Omani, Kuwaiti, Sudanese and Turkish. Most common genetic variant in all populations was the VKORC1 (-1639G>A), with a minor allele frequency ranging from 30% in Egyptians and up to 52% and 56% in Lebanese and Iranian, respectively. Variants in the CYP2C9 were less common, with the highest MAF for CYP2C9*2 among Iranians (27%). Variants in the VKORC1 and CYP2C9 were the most significant predictors of warfarin dose in all populations. Along with other genetic and non-genetic factors, they explained up to 63% of the dose variability in Omani and Israeli patients. Variants of VKORC1 and CYP2C9 are the strongest predictors of warfarin dose variability among the different populations from MENA. Although many of those populations share the same ancestry and are similar in their warfarin dose predictors, a population specific dosing algorithm is needed for the prospective estimation of warfarin

  14. Beam-column joint shear prediction using hybridized deep learning neural network with genetic algorithm

    Science.gov (United States)

    Mundher Yaseen, Zaher; Abdulmohsin Afan, Haitham; Tran, Minh-Tung

    2018-04-01

    Scientifically evidenced that beam-column joints are a critical point in the reinforced concrete (RC) structure under the fluctuation loads effects. In this novel hybrid data-intelligence model developed to predict the joint shear behavior of exterior beam-column structure frame. The hybrid data-intelligence model is called genetic algorithm integrated with deep learning neural network model (GA-DLNN). The genetic algorithm is used as prior modelling phase for the input approximation whereas the DLNN predictive model is used for the prediction phase. To demonstrate this structural problem, experimental data is collected from the literature that defined the dimensional and specimens’ properties. The attained findings evidenced the efficitveness of the hybrid GA-DLNN in modelling beam-column joint shear problem. In addition, the accurate prediction achived with less input variables owing to the feasibility of the evolutionary phase.

  15. The Current and Future Use of Ridge Regression for Prediction in Quantitative Genetics

    Directory of Open Access Journals (Sweden)

    Ronald de Vlaming

    2015-01-01

    Full Text Available In recent years, there has been a considerable amount of research on the use of regularization methods for inference and prediction in quantitative genetics. Such research mostly focuses on selection of markers and shrinkage of their effects. In this review paper, the use of ridge regression for prediction in quantitative genetics using single-nucleotide polymorphism data is discussed. In particular, we consider (i the theoretical foundations of ridge regression, (ii its link to commonly used methods in animal breeding, (iii the computational feasibility, and (iv the scope for constructing prediction models with nonlinear effects (e.g., dominance and epistasis. Based on a simulation study we gauge the current and future potential of ridge regression for prediction of human traits using genome-wide SNP data. We conclude that, for outcomes with a relatively simple genetic architecture, given current sample sizes in most cohorts (i.e., N<10,000 the predictive accuracy of ridge regression is slightly higher than the classical genome-wide association study approach of repeated simple regression (i.e., one regression per SNP. However, both capture only a small proportion of the heritability. Nevertheless, we find evidence that for large-scale initiatives, such as biobanks, sample sizes can be achieved where ridge regression compared to the classical approach improves predictive accuracy substantially.

  16. Genetic alterations within the DENND1A gene in patients with polycystic ovary syndrome (PCOS.

    Directory of Open Access Journals (Sweden)

    Mette B Eriksen

    Full Text Available Polycystic ovary syndrome (PCOS, the most common endocrine disease among premenopausal women, is caused by both genes and environment. We and others previously reported association between single nucleotide polymorphisms (SNPs in the DENND1A gene and PCOS. We therefore sequenced the DENND1A gene in white patients with PCOS to identify possible alterations that may be implicated in the PCOS pathogenesis. Patients were referred with PCOS and/or hirsutism between 1998 and 2011 (n = 261. PCOS was diagnosed according to the Rotterdam criteria (n = 165. Sequence analysis was performed in 10 patients with PCOS. Additional patients (n = 251 and healthy female controls (n = 248 were included for SNP genotyping. Patients underwent clinical examination including Ferriman-Gallwey score (FG-score, biochemical analyses and transvaginal ultrasound. Mutation analysis was carried out by bidirectional sequencing. SNP genotyping was tested by allelic discrimination in real-time PCR in the additional patients and controls. Sequencing of the DENND1A gene identified eight SNPs; seven were not known to be associated with any diseases. One missense SNP was detected (rs189947178, A/C, potentially altering the structural conformation of the DENND1A protein. SNP genotyping of rs189947178 showed significantly more carriers among patients with PCOS and moderate hirsutism compared to controls. However, due to small sample size and lack of multiple regression analysis supporting an association between rs189947178 and FG-score or PCOS diagnosis, this could be a false positive finding. In conclusion, sequence analysis of the DENND1A gene of patients with PCOS did not identify alterations that alone could be responsible for the PCOS pathogenesis, but a missense SNP (rs189947178 was identified in one patient and significantly more carriers of rs189947178 were found among patients with PCOS and moderate hirsutism vs. controls. Additional studies with independent cohort are needed

  17. Assessing glycolytic flux alterations resulting from genetic perturbations in E. coli using a biosensor

    DEFF Research Database (Denmark)

    Lehning, Christina Eva; Siedler, Solvej; Ellabaan, Mostafa M Hashim

    2017-01-01

    validated the glycolytic flux dependency of the biosensor in a range of different carbon sources in six different E. coli strains and during mevalonate production. Furthermore, we studied the flux-altering effects of genome-wide single gene knock-outs in E. coli in a multiplex FlowSeq experiment. From...... a library consisting of 2126 knock-out mutants, we identified 3 mutants with high-flux and 95 mutants with low-flux phenotypes that did not have severe growth defects. This approach can improve our understanding of glycolytic flux regulation improving metabolic models and engineering efforts....

  18. Simulation, prediction, and genetic analyses of daily methane emissions in dairy cattle.

    Science.gov (United States)

    Yin, T; Pinent, T; Brügemann, K; Simianer, H; König, S

    2015-08-01

    This study presents an approach combining phenotypes from novel traits, deterministic equations from cattle nutrition, and stochastic simulation techniques from animal breeding to generate test-day methane emissions (MEm) of dairy cows. Data included test-day production traits (milk yield, fat percentage, protein percentage, milk urea nitrogen), conformation traits (wither height, hip width, body condition score), female fertility traits (days open, calving interval, stillbirth), and health traits (clinical mastitis) from 961 first lactation Brown Swiss cows kept on 41 low-input farms in Switzerland. Test-day MEm were predicted based on the traits from the current data set and 2 deterministic prediction equations, resulting in the traits labeled MEm1 and MEm2. Stochastic simulations were used to assign individual concentrate intake in dependency of farm-type specifications (requirement when calculating MEm2). Genetic parameters for MEm1 and MEm2 were estimated using random regression models. Predicted MEm had moderate heritabilities over lactation and ranged from 0.15 to 0.37, with highest heritabilities around DIM 100. Genetic correlations between MEm1 and MEm2 ranged between 0.91 and 0.94. Antagonistic genetic correlations in the range from 0.70 to 0.92 were found for the associations between MEm2 and milk yield. Genetic correlations between MEm with days open and with calving interval increased from 0.10 at the beginning to 0.90 at the end of lactation. Genetic relationships between MEm2 and stillbirth were negative (0 to -0.24) from the beginning to the peak phase of lactation. Positive genetic relationships in the range from 0.02 to 0.49 were found between MEm2 with clinical mastitis. Interpretation of genetic (co)variance components should also consider the limitations when using data generated by prediction equations. Prediction functions only describe that part of MEm which is dependent on the factors and effects included in the function. With high

  19. Endogenous network states predict gain or loss of functions for genetic mutations in hepatocellular carcinoma.

    Science.gov (United States)

    Wang, Gaowei; Su, Hang; Yu, Helin; Yuan, Ruoshi; Zhu, Xiaomei; Ao, Ping

    2016-02-01

    Cancers have been typically characterized by genetic mutations. Patterns of such mutations have traditionally been analysed by posteriori statistical association approaches. One may ponder the possibility of a priori determination of any mutation regularity. Here by exploring biological processes implied in a mechanistic theory recently developed (the endogenous molecular-cellular network theory), we found that the features of genetic mutations in cancers may be predicted without any prior knowledge of mutation propensities. With hepatocellular carcinoma (HCC) as an example, we found that the normal hepatocyte and cancerous hepatocyte can be represented by robust stable states of one single endogenous network. These stable states, specified by distinct patterns of expressions or activities of proteins in the network, provide means to directly identify a set of most probable genetic mutations and their effects in HCC. As the key proteins and main interactions in the network are conserved through cell types in an organism, similar mutational features may also be found in other cancers. This analysis yielded straightforward and testable predictions on accumulated and preferred mutation spectra in normal tissue. The validation of predicted cancer state mutation patterns demonstrates the usefulness and potential of a causal dynamical framework to understand and predict genetic mutations in cancer. © 2016 The Author(s).

  20. Logistics for Working Together to Facilitate Genomic/Quantitative Genetic Prediction

    Science.gov (United States)

    The incorporation of DNA tests into the national cattle evaluation system will require estimation of variances of and covariances among the additive genetic components of the DNA tests and the phenotypic traits they are intended to predict. Populations with both DNA test results and phenotypes will ...

  1. Genetic Counseling and Cardiac Care in Predictively Tested Hypertrophic Cardiomyopathy Mutation Carriers: The Patients' Perspective

    NARCIS (Netherlands)

    Christiaans, Imke; van Langen, Irene M.; Birnie, Erwin; Bonsel, Gouke J.; Wilde, Arthur A. M.; Smets, Ellen M. A.

    2009-01-01

    Hypertrophic cardiomyopathy (HCM) is a common hereditary heart disease associated with sudden cardiac death. predictive genetic counseling and testing are performed using adapted Huntington guidelines, that is, psychosocial care and time for reflection are not obligatory and the test result can be

  2. Genetic vulnerability interacts with parenting and early care education to predict increasing externalizing behavior.

    Science.gov (United States)

    Lipscomb, Shannon T; Laurent, Heidemarie; Neiderhiser, Jenae M; Shaw, Daniel S; Natsuaki, Misaki N; Reiss, David; Leve, Leslie D

    2014-01-01

    The current study examined interactions among genetic influences and children's early environments on the development of externalizing behaviors from 18 months to 6 years of age. Participants included 233 families linked through adoption (birth parents and adoptive families). Genetic influences were assessed by birth parent temperamental regulation. Early environments included both family (overreactive parenting) and out-of-home factors (center-based Early Care and Education; ECE). Overreactive parenting predicted more child externalizing behaviors. Attending center-based ECE was associated with increasing externalizing behaviors only for children with genetic liability for dysregulation. Additionally, children who were at risk for externalizing behaviors due to both genetic variability and exposure to center-based ECE were more sensitive to the effects of overreactive parenting on externalizing behavior than other children.

  3. Factors Motivating Individuals to Consider Genetic Testing for Type 2 Diabetes Risk Prediction.

    Directory of Open Access Journals (Sweden)

    Jennifer Wessel

    Full Text Available The purpose of this study was to identify attitudes and perceptions of willingness to participate in genetic testing for type 2 diabetes (T2D risk prediction in the general population. Adults (n = 598 were surveyed on attitudes about utilizing genetic testing to predict future risk of T2D. Participants were recruited from public libraries (53%, online registry (37% and a safety net hospital emergency department (10%. Respondents were 37 ± 11 years old, primarily White (54%, female (69%, college educated (46%, with an annual income ≥$25,000 (56%. Half of participants were interested in genetic testing for T2D (52% and 81% agreed/strongly agreed genetic testing should be available to the public. Only 57% of individuals knew T2D is preventable. A multivariate model to predict interest in genetic testing was adjusted for age, gender, recruitment location and BMI; significant predictors were motivation (high perceived personal risk of T2D [OR = 4.38 (1.76, 10.9]; family history [OR = 2.56 (1.46, 4.48]; desire to know risk prior to disease onset [OR = 3.25 (1.94, 5.42]; and knowing T2D is preventable [OR = 2.11 (1.24, 3.60], intention (if the cost is free [OR = 10.2 (4.27, 24.6]; and learning T2D is preventable [OR = 5.18 (1.95, 13.7] and trust of genetic testing results [OR = 0.03 (0.003, 0.30]. Individuals are interested in genetic testing for T2D risk which offers unique information that is personalized. Financial accessibility, validity of the test and availability of diabetes prevention programs were identified as predictors of interest in T2D testing.

  4. Novel applications of multitask learning and multiple output regression to multiple genetic trait prediction.

    Science.gov (United States)

    He, Dan; Kuhn, David; Parida, Laxmi

    2016-06-15

    Given a set of biallelic molecular markers, such as SNPs, with genotype values encoded numerically on a collection of plant, animal or human samples, the goal of genetic trait prediction is to predict the quantitative trait values by simultaneously modeling all marker effects. Genetic trait prediction is usually represented as linear regression models. In many cases, for the same set of samples and markers, multiple traits are observed. Some of these traits might be correlated with each other. Therefore, modeling all the multiple traits together may improve the prediction accuracy. In this work, we view the multitrait prediction problem from a machine learning angle: as either a multitask learning problem or a multiple output regression problem, depending on whether different traits share the same genotype matrix or not. We then adapted multitask learning algorithms and multiple output regression algorithms to solve the multitrait prediction problem. We proposed a few strategies to improve the least square error of the prediction from these algorithms. Our experiments show that modeling multiple traits together could improve the prediction accuracy for correlated traits. The programs we used are either public or directly from the referred authors, such as MALSAR (http://www.public.asu.edu/~jye02/Software/MALSAR/) package. The Avocado data set has not been published yet and is available upon request. dhe@us.ibm.com. © The Author 2016. Published by Oxford University Press.

  5. Screw Remaining Life Prediction Based on Quantum Genetic Algorithm and Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Xiaochen Zhang

    2017-01-01

    Full Text Available To predict the remaining life of ball screw, a screw remaining life prediction method based on quantum genetic algorithm (QGA and support vector machine (SVM is proposed. A screw accelerated test bench is introduced. Accelerometers are installed to monitor the performance degradation of ball screw. Combined with wavelet packet decomposition and isometric mapping (Isomap, the sensitive feature vectors are obtained and stored in database. Meanwhile, the sensitive feature vectors are randomly chosen from the database and constitute training samples and testing samples. Then the optimal kernel function parameter and penalty factor of SVM are searched with the method of QGA. Finally, the training samples are used to train optimized SVM while testing samples are adopted to test the prediction accuracy of the trained SVM so the screw remaining life prediction model can be got. The experiment results show that the screw remaining life prediction model could effectively predict screw remaining life.

  6. Melanoma risk prediction using a multilocus genetic risk score in the Women's Health Initiative cohort.

    Science.gov (United States)

    Cho, Hyunje G; Ransohoff, Katherine J; Yang, Lingyao; Hedlin, Haley; Assimes, Themistocles; Han, Jiali; Stefanick, Marcia; Tang, Jean Y; Sarin, Kavita Y

    2018-07-01

    Single-nucleotide polymorphisms (SNPs) associated with melanoma have been identified though genome-wide association studies. However, the combined impact of these SNPs on melanoma development remains unclear, particularly in postmenopausal women who carry a lower melanoma risk. We examine the contribution of a combined polygenic risk score on melanoma development in postmenopausal women. Genetic risk scores were calculated using 21 genome-wide association study-significant SNPs. Their combined effect on melanoma development was evaluated in 19,102 postmenopausal white women in the clinical trial and observational study arms of the Women's Health Initiative dataset. Compared to the tertile of weighted genetic risk score with the lowest genetic risk, the women in the tertile with the highest genetic risk were 1.9 times more likely to develop melanoma (95% confidence interval 1.50-2.42). The incremental change in c-index from adding genetic risk scores to age were 0.075 (95% confidence interval 0.041-0.109) for incident melanoma. Limitations include a lack of information on nevi count, Fitzpatrick skin type, family history of melanoma, and potential reporting and selection bias in the Women's Health Initiative cohort. Higher genetic risk is associated with increased melanoma prevalence and incidence in postmenopausal women, but current genetic information may have a limited role in risk prediction when phenotypic information is available. Copyright © 2018 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.

  7. Genetic algorithm based adaptive neural network ensemble and its application in predicting carbon flux

    Science.gov (United States)

    Xue, Y.; Liu, S.; Hu, Y.; Yang, J.; Chen, Q.

    2007-01-01

    To improve the accuracy in prediction, Genetic Algorithm based Adaptive Neural Network Ensemble (GA-ANNE) is presented. Intersections are allowed between different training sets based on the fuzzy clustering analysis, which ensures the diversity as well as the accuracy of individual Neural Networks (NNs). Moreover, to improve the accuracy of the adaptive weights of individual NNs, GA is used to optimize the cluster centers. Empirical results in predicting carbon flux of Duke Forest reveal that GA-ANNE can predict the carbon flux more accurately than Radial Basis Function Neural Network (RBFNN), Bagging NN ensemble, and ANNE. ?? 2007 IEEE.

  8. Crystal structure prediction of flexible molecules using parallel genetic algorithms with a standard force field.

    Science.gov (United States)

    Kim, Seonah; Orendt, Anita M; Ferraro, Marta B; Facelli, Julio C

    2009-10-01

    This article describes the application of our distributed computing framework for crystal structure prediction (CSP) the modified genetic algorithms for crystal and cluster prediction (MGAC), to predict the crystal structure of flexible molecules using the general Amber force field (GAFF) and the CHARMM program. The MGAC distributed computing framework includes a series of tightly integrated computer programs for generating the molecule's force field, sampling crystal structures using a distributed parallel genetic algorithm and local energy minimization of the structures followed by the classifying, sorting, and archiving of the most relevant structures. Our results indicate that the method can consistently find the experimentally known crystal structures of flexible molecules, but the number of missing structures and poor ranking observed in some crystals show the need for further improvement of the potential. Copyright 2009 Wiley Periodicals, Inc.

  9. Alteration of Box-Jenkins methodology by implementing genetic algorithm method

    Science.gov (United States)

    Ismail, Zuhaimy; Maarof, Mohd Zulariffin Md; Fadzli, Mohammad

    2015-02-01

    A time series is a set of values sequentially observed through time. The Box-Jenkins methodology is a systematic method of identifying, fitting, checking and using integrated autoregressive moving average time series model for forecasting. Box-Jenkins method is an appropriate for a medium to a long length (at least 50) time series data observation. When modeling a medium to a long length (at least 50), the difficulty arose in choosing the accurate order of model identification level and to discover the right parameter estimation. This presents the development of Genetic Algorithm heuristic method in solving the identification and estimation models problems in Box-Jenkins. Data on International Tourist arrivals to Malaysia were used to illustrate the effectiveness of this proposed method. The forecast results that generated from this proposed model outperformed single traditional Box-Jenkins model.

  10. Genetic and Epigenetic Alterations of Brassica nigra Introgression Lines from Somatic Hybridization: A Resource for Cauliflower Improvement.

    Science.gov (United States)

    Wang, Gui-Xiang; Lv, Jing; Zhang, Jie; Han, Shuo; Zong, Mei; Guo, Ning; Zeng, Xing-Ying; Zhang, Yue-Yun; Wang, You-Ping; Liu, Fan

    2016-01-01

    Broad phenotypic variations were obtained previously in derivatives from the asymmetric somatic hybridization of cauliflower "Korso" (Brassica oleracea var. botrytis, 2n = 18, CC genome) and black mustard "G1/1" (Brassica nigra, 2n = 16, BB genome). However, the mechanisms underlying these variations were unknown. In this study, 28 putative introgression lines (ILs) were pre-selected according to a series of morphological (leaf shape and color, plant height and branching, curd features, and flower traits) and physiological (black rot/club root resistance) characters. Multi-color fluorescence in situ hybridization revealed that these plants contained 18 chromosomes derived from "Korso." Molecular marker (65 simple sequence repeats and 77 amplified fragment length polymorphisms) analysis identified the presence of "G1/1" DNA segments (average 7.5%). Additionally, DNA profiling revealed many genetic and epigenetic differences among the ILs, including sequence alterations, deletions, and variation in patterns of cytosine methylation. The frequency of fragments lost (5.1%) was higher than presence of novel bands (1.4%), and the presence of fragments specific to Brassica carinata (BBCC 2n = 34) were common (average 15.5%). Methylation-sensitive amplified polymorphism analysis indicated that methylation changes were common and that hypermethylation (12.4%) was more frequent than hypomethylation (4.8%). Our results suggested that asymmetric somatic hybridization and alien DNA introgression induced genetic and epigenetic alterations. Thus, these ILs represent an important, novel germplasm resource for cauliflower improvement that can be mined for diverse traits of interest to breeders and researchers.

  11. Genetic and epigenetic alterations of Brassica nigra introgression lines from somatic hybridization: a resource for cauliflower improvement

    Directory of Open Access Journals (Sweden)

    Guixiang Wang

    2016-08-01

    Full Text Available Broad phenotypic variations were obtained previously in derivatives from the asymmetric somatic hybridization of cauliflower ‘Korso’ (Brassica oleracea var. botrytis, 2n = 18, CC genome and black mustard ‘G1/1’ (Brassica nigra, 2n = 16, BB genome. However, the mechanisms underlying these variations were unknown. In this study, 28 putative introgression lines (ILs were pre-selected according to a series of morphological (leaf shape and color, plant height and branching, curd features, and flower traits and physiological (black rot/club root resistance characters. Multi-color fluorescence in situ hybridization revealed that these plants contained 18 chromosomes derived from ‘Korso’. Molecular marker (65 simple sequence repeats and 77 amplified fragment length polymorphisms analysis identified the presence of ‘G1/1’ DNA segments (average 7.5%. Additionally, DNA profiling revealed many genetic and epigenetic differences among the ILs, including sequence alterations, deletions, and variation in patterns of cytosine methylation. The frequency of fragments lost (5.1% was significantly higher than presence of novel bands (1.4%, and the presence of fragments specific to B. carinata (BBCC 2n = 34 were common (average 15.5%. Methylation-sensitive amplified polymorphism analysis indicated that methylation changes were common and that hypermethylation (12.4% was more frequent than hypomethylation (4.8%. Our results suggested that asymmetric somatic hybridization and alien DNA introgression induced genetic and epigenetic alterations. Thus, these ILs represent an important, novel germplasm resource for cauliflower improvement that can be mined for diverse traits of interest to breeders and researchers.

  12. Intraspecific morphological and genetic variation of common species predicts ranges of threatened ones

    Science.gov (United States)

    Fuller, Trevon L.; Thomassen, Henri A.; Peralvo, Manuel; Buermann, Wolfgang; Milá, Borja; Kieswetter, Charles M.; Jarrín-V, Pablo; Devitt, Susan E. Cameron; Mason, Eliza; Schweizer, Rena M.; Schlunegger, Jasmin; Chan, Janice; Wang, Ophelia; Schneider, Christopher J.; Pollinger, John P.; Saatchi, Sassan; Graham, Catherine H.; Wayne, Robert K.; Smith, Thomas B.

    2013-01-01

    Predicting where threatened species occur is useful for making informed conservation decisions. However, because they are usually rare, surveying threatened species is often expensive and time intensive. Here, we show how regions where common species exhibit high genetic and morphological divergence among populations can be used to predict the occurrence of species of conservation concern. Intraspecific variation of common species of birds, bats and frogs from Ecuador were found to be a significantly better predictor for the occurrence of threatened species than suites of environmental variables or the occurrence of amphibians and birds. Fully 93 per cent of the threatened species analysed had their range adequately represented by the geographical distribution of the morphological and genetic variation found in seven common species. Both higher numbers of threatened species and greater genetic and morphological variation of common species occurred along elevation gradients. Higher levels of intraspecific divergence may be the result of disruptive selection and/or introgression along gradients. We suggest that collecting data on genetic and morphological variation in common species can be a cost effective tool for conservation planning, and that future biodiversity inventories include surveying genetic and morphological data of common species whenever feasible. PMID:23595273

  13. Predictive Psychiatric Genetic Testing in Minors: An Exploration of the Non-Medical Benefits.

    Science.gov (United States)

    Manzini, Arianna; Vears, Danya F

    2018-03-01

    Predictive genetic testing for susceptibility to psychiatric conditions is likely to become part of standard practice. Because the onset of most psychiatric diseases is in late adolescence or early adulthood, testing minors could lead to early identification that may prevent or delay the development of these disorders. However, due to their complex aetiology, psychiatric genetic testing does not provide the immediate medical benefits that current guidelines require for testing minors. While several authors have argued non-medical benefits may play a crucial role in favour of predictive testing for other conditions, little research has explored such a role in psychiatric disorders. This paper outlines the potential non-medical benefits and harms of psychiatric genetic testing in minors in order to consider whether the non-medical benefits could ever make such testing appropriate. Five non-medical themes arise in the literature: psychological impacts, autonomy/self-determination, implications of the biomedical approach, use of financial and intellectual resources, and discrimination. Non-medical benefits were prominent in all of them, suggesting that psychiatric genetic testing in minors may be appropriate in some circumstances. Further research needs to empirically assess these potential non-medical benefits, incorporate minors in the debate, and include normative reflection to evaluate the very purposes and motivations of psychiatric genetic testing in minors.

  14. Prediction of genetic values of quantitative traits with epistatic effects in plant breeding populations.

    Science.gov (United States)

    Wang, D; Salah El-Basyoni, I; Stephen Baenziger, P; Crossa, J; Eskridge, K M; Dweikat, I

    2012-11-01

    Though epistasis has long been postulated to have a critical role in genetic regulation of important pathways as well as provide a major source of variation in the process of speciation, the importance of epistasis for genomic selection in the context of plant breeding is still being debated. In this paper, we report the results on the prediction of genetic values with epistatic effects for 280 accessions in the Nebraska Wheat Breeding Program using adaptive mixed least absolute shrinkage and selection operator (LASSO). The development of adaptive mixed LASSO, originally designed for association mapping, for the context of genomic selection is reported. The results show that adaptive mixed LASSO can be successfully applied to the prediction of genetic values while incorporating both marker main effects and epistatic effects. Especially, the prediction accuracy is substantially improved by the inclusion of two-locus epistatic effects (more than onefold in some cases as measured by cross-validation correlation coefficient), which is observed for multiple traits and planting locations. This points to significant potential in using non-additive genetic effects for genomic selection in crop breeding practices.

  15. Genetic alterations in fatty acid transport and metabolism genes are associated with metastatic progression and poor prognosis of human cancers.

    Science.gov (United States)

    Nath, Aritro; Chan, Christina

    2016-01-04

    Reprogramming of cellular metabolism is a hallmark feature of cancer cells. While a distinct set of processes drive metastasis when compared to tumorigenesis, it is yet unclear if genetic alterations in metabolic pathways are associated with metastatic progression of human cancers. Here, we analyzed the mutation, copy number variation and gene expression patterns of a literature-derived model of metabolic genes associated with glycolysis (Warburg effect), fatty acid metabolism (lipogenesis, oxidation, lipolysis, esterification) and fatty acid uptake in >9000 primary or metastatic tumor samples from the multi-cancer TCGA datasets. Our association analysis revealed a uniform pattern of Warburg effect mutations influencing prognosis across all tumor types, while copy number alterations in the electron transport chain gene SCO2, fatty acid uptake (CAV1, CD36) and lipogenesis (PPARA, PPARD, MLXIPL) genes were enriched in metastatic tumors. Using gene expression profiles, we established a gene-signature (CAV1, CD36, MLXIPL, CPT1C, CYP2E1) that strongly associated with epithelial-mesenchymal program across multiple cancers. Moreover, stratification of samples based on the copy number or expression profiles of the genes identified in our analysis revealed a significant effect on patient survival rates, thus confirming prominent roles of fatty acid uptake and metabolism in metastatic progression and poor prognosis of human cancers.

  16. Genetic transformation of rare Verbascum eriophorum Godr. plants and metabolic alterations revealed by NMR-based metabolomics.

    Science.gov (United States)

    Marchev, Andrey; Yordanova, Zhenya; Alipieva, Kalina; Zahmanov, Georgi; Rusinova-Videva, Snezhana; Kapchina-Toteva, Veneta; Simova, Svetlana; Popova, Milena; Georgiev, Milen I

    2016-09-01

    To develop a protocol to transform Verbascum eriophorum and to study the metabolic differences between mother plants and hairy root culture by applying NMR and processing the datasets with chemometric tools. Verbascum eriophorum is a rare species with restricted distribution, which is poorly studied. Agrobacterium rhizogenes-mediated genetic transformation of V. eriophorum and hairy root culture induction are reported for the first time. To determine metabolic alterations, V. eriophorum mother plants and relevant hairy root culture were subjected to comprehensive metabolomic analyses, using NMR (1D and 2D). Metabolomics data, processed using chemometric tools (and principal component analysis in particular) allowed exploration of V. eriophorum metabolome and have enabled identification of verbascoside (by means of 2D-TOCSY NMR) as the most abundant compound in hairy root culture. Metabolomics data contribute to the elucidation of metabolic alterations after T-DNA transfer to the host V. eriophorum genome and the development of hairy root culture for sustainable bioproduction of high value verbascoside.

  17. Genetic Gain Increases by Applying the Usefulness Criterion with Improved Variance Prediction in Selection of Crosses.

    Science.gov (United States)

    Lehermeier, Christina; Teyssèdre, Simon; Schön, Chris-Carolin

    2017-12-01

    A crucial step in plant breeding is the selection and combination of parents to form new crosses. Genome-based prediction guides the selection of high-performing parental lines in many crop breeding programs which ensures a high mean performance of progeny. To warrant maximum selection progress, a new cross should also provide a large progeny variance. The usefulness concept as measure of the gain that can be obtained from a specific cross accounts for variation in progeny variance. Here, it is shown that genetic gain can be considerably increased when crosses are selected based on their genomic usefulness criterion compared to selection based on mean genomic estimated breeding values. An efficient and improved method to predict the genetic variance of a cross based on Markov chain Monte Carlo samples of marker effects from a whole-genome regression model is suggested. In simulations representing selection procedures in crop breeding programs, the performance of this novel approach is compared with existing methods, like selection based on mean genomic estimated breeding values and optimal haploid values. In all cases, higher genetic gain was obtained compared with previously suggested methods. When 1% of progenies per cross were selected, the genetic gain based on the estimated usefulness criterion increased by 0.14 genetic standard deviation compared to a selection based on mean genomic estimated breeding values. Analytical derivations of the progeny genotypic variance-covariance matrix based on parental genotypes and genetic map information make simulations of progeny dispensable, and allow fast implementation in large-scale breeding programs. Copyright © 2017 by the Genetics Society of America.

  18. Estimating additive and non-additive genetic variances and predicting genetic merits using genome-wide dense single nucleotide polymorphism markers.

    Directory of Open Access Journals (Sweden)

    Guosheng Su

    Full Text Available Non-additive genetic variation is usually ignored when genome-wide markers are used to study the genetic architecture and genomic prediction of complex traits in human, wild life, model organisms or farm animals. However, non-additive genetic effects may have an important contribution to total genetic variation of complex traits. This study presented a genomic BLUP model including additive and non-additive genetic effects, in which additive and non-additive genetic relation matrices were constructed from information of genome-wide dense single nucleotide polymorphism (SNP markers. In addition, this study for the first time proposed a method to construct dominance relationship matrix using SNP markers and demonstrated it in detail. The proposed model was implemented to investigate the amounts of additive genetic, dominance and epistatic variations, and assessed the accuracy and unbiasedness of genomic predictions for daily gain in pigs. In the analysis of daily gain, four linear models were used: 1 a simple additive genetic model (MA, 2 a model including both additive and additive by additive epistatic genetic effects (MAE, 3 a model including both additive and dominance genetic effects (MAD, and 4 a full model including all three genetic components (MAED. Estimates of narrow-sense heritability were 0.397, 0.373, 0.379 and 0.357 for models MA, MAE, MAD and MAED, respectively. Estimated dominance variance and additive by additive epistatic variance accounted for 5.6% and 9.5% of the total phenotypic variance, respectively. Based on model MAED, the estimate of broad-sense heritability was 0.506. Reliabilities of genomic predicted breeding values for the animals without performance records were 28.5%, 28.8%, 29.2% and 29.5% for models MA, MAE, MAD and MAED, respectively. In addition, models including non-additive genetic effects improved unbiasedness of genomic predictions.

  19. An altered redox balance and increased genetic instability characterize primary fibroblasts derived from xeroderma pigmentosum group A patients

    International Nuclear Information System (INIS)

    Parlanti, Eleonora; Pietraforte, Donatella; Iorio, Egidio; Visentin, Sergio; De Nuccio, Chiara; Zijno, Andrea; D’Errico, Mariarosaria; Simonelli, Valeria; Sanchez, Massimo; Fattibene, Paola; Falchi, Mario; Dogliotti, Eugenia

    2015-01-01

    Highlights: • Increased levels and different types of intracellular radical species as well as an altered glutathione redox state characterize XP-A human cells when compared to normal. • A more glycolytic metabolism and higher ATP levels are associated with alteration of mitochondrial morphology and response to mitochondrial toxicants when XPA is defective. • XP-A human cells show increased spontaneous micronuclei frequency, a hallmark of cancer risk. - Abstract: Xeroderma pigmentosum (XP)-A patients are characterized by increased solar skin carcinogenesis and present also neurodegeneration. XPA deficiency is associated with defective nucleotide excision repair (NER) and increased basal levels of oxidatively induced DNA damage. In this study we search for the origin of increased levels of oxidatively generated DNA lesions in XP-A cell genome and then address the question of whether increased oxidative stress might drive genetic instability. We show that XP-A human primary fibroblasts present increased levels and different types of intracellular reactive oxygen species (ROS) as compared to normal fibroblasts, with O_2_−· and H_2O_2 being the major reactive species. Moreover, XP-A cells are characterized by decreased reduced glutathione (GSH)/oxidized glutathione (GSSG) ratios as compared to normal fibroblasts. The significant increase of ROS levels and the alteration of the glutathione redox state following silencing of XPA confirmed the causal relationship between a functional XPA and the control of redox balance. Proton nuclear magnetic resonance ("1H NMR) analysis of the metabolic profile revealed a more glycolytic metabolism and higher ATP levels in XP-A than in normal primary fibroblasts. This perturbation of bioenergetics is associated with different morphology and response of mitochondria to targeted toxicants. In line with cancer susceptibility, XP-A primary fibroblasts showed increased spontaneous micronuclei (MN) frequency, a hallmark of cancer

  20. An altered redox balance and increased genetic instability characterize primary fibroblasts derived from xeroderma pigmentosum group A patients

    Energy Technology Data Exchange (ETDEWEB)

    Parlanti, Eleonora [Department of Environment and Primary Prevention, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome (Italy); Pietraforte, Donatella; Iorio, Egidio; Visentin, Sergio; De Nuccio, Chiara [Department of Cell Biology and Neurosciences, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome (Italy); Zijno, Andrea; D’Errico, Mariarosaria; Simonelli, Valeria [Department of Environment and Primary Prevention, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome (Italy); Sanchez, Massimo [Department of Cell Biology and Neurosciences, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome (Italy); Fattibene, Paola [Department of Technology and Health, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome (Italy); Falchi, Mario [National AIDS Center, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome (Italy); Dogliotti, Eugenia, E-mail: dogliotti@iss.it [Department of Environment and Primary Prevention, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome (Italy)

    2015-12-15

    Highlights: • Increased levels and different types of intracellular radical species as well as an altered glutathione redox state characterize XP-A human cells when compared to normal. • A more glycolytic metabolism and higher ATP levels are associated with alteration of mitochondrial morphology and response to mitochondrial toxicants when XPA is defective. • XP-A human cells show increased spontaneous micronuclei frequency, a hallmark of cancer risk. - Abstract: Xeroderma pigmentosum (XP)-A patients are characterized by increased solar skin carcinogenesis and present also neurodegeneration. XPA deficiency is associated with defective nucleotide excision repair (NER) and increased basal levels of oxidatively induced DNA damage. In this study we search for the origin of increased levels of oxidatively generated DNA lesions in XP-A cell genome and then address the question of whether increased oxidative stress might drive genetic instability. We show that XP-A human primary fibroblasts present increased levels and different types of intracellular reactive oxygen species (ROS) as compared to normal fibroblasts, with O{sub 2−}· and H{sub 2}O{sub 2} being the major reactive species. Moreover, XP-A cells are characterized by decreased reduced glutathione (GSH)/oxidized glutathione (GSSG) ratios as compared to normal fibroblasts. The significant increase of ROS levels and the alteration of the glutathione redox state following silencing of XPA confirmed the causal relationship between a functional XPA and the control of redox balance. Proton nuclear magnetic resonance ({sup 1}H NMR) analysis of the metabolic profile revealed a more glycolytic metabolism and higher ATP levels in XP-A than in normal primary fibroblasts. This perturbation of bioenergetics is associated with different morphology and response of mitochondria to targeted toxicants. In line with cancer susceptibility, XP-A primary fibroblasts showed increased spontaneous micronuclei (MN) frequency, a

  1. Exploitation of genetic interaction network topology for the prediction of epistatic behavior

    KAUST Repository

    Alanis Lobato, Gregorio

    2013-10-01

    Genetic interaction (GI) detection impacts the understanding of human disease and the ability to design personalized treatment. The mapping of every GI in most organisms is far from complete due to the combinatorial amount of gene deletions and knockdowns required. Computational techniques to predict new interactions based only on network topology have been developed in network science but never applied to GI networks.We show that topological prediction of GIs is possible with high precision and propose a graph dissimilarity index that is able to provide robust prediction in both dense and sparse networks.Computational prediction of GIs is a strong tool to aid high-throughput GI determination. The dissimilarity index we propose in this article is able to attain precise predictions that reduce the universe of candidate GIs to test in the lab. © 2013 Elsevier Inc.

  2. Exploitation of genetic interaction network topology for the prediction of epistatic behavior

    KAUST Repository

    Alanis Lobato, Gregorio; Cannistraci, Carlo; Ravasi, Timothy

    2013-01-01

    Genetic interaction (GI) detection impacts the understanding of human disease and the ability to design personalized treatment. The mapping of every GI in most organisms is far from complete due to the combinatorial amount of gene deletions and knockdowns required. Computational techniques to predict new interactions based only on network topology have been developed in network science but never applied to GI networks.We show that topological prediction of GIs is possible with high precision and propose a graph dissimilarity index that is able to provide robust prediction in both dense and sparse networks.Computational prediction of GIs is a strong tool to aid high-throughput GI determination. The dissimilarity index we propose in this article is able to attain precise predictions that reduce the universe of candidate GIs to test in the lab. © 2013 Elsevier Inc.

  3. The genetic basis for altered blood vessel function in disease: large artery stiffening

    Directory of Open Access Journals (Sweden)

    Alex Agrotis

    2005-12-01

    Full Text Available Alex AgrotisThe Cell Biology Laboratory, Baker Heart Research Institute, Melbourne, Victoria, AustraliaAbstract: The progressive stiffening of the large arteries in humans that occurs during aging constitutes a potential risk factor for increased cardiovascular morbidity and mortality, and is accompanied by an elevation in systolic blood pressure and pulse pressure. While the underlying basis for these changes remains to be fully elucidated, factors that are able to influence the structure and composition of the extracellular matrix and the way it interacts with arterial smooth muscle cells could profoundly affect the properties of the large arteries. Thus, while age and sex represent important factors contributing to large artery stiffening, the variation in growth-stimulating factors and those that modulate extracellular production and homeostasis are also being increasingly recognized to play a key role in the process. Therefore, elucidating the contribution that genetic variation makes to large artery stiffening could ultimately provide the basis for clinical strategies designed to regulate the process for therapeutic benefit.Keywords: arterial stiffness, genes, polymorphism, extracellular matrix proteins

  4. Uncoupling of Metabolic Health from Longevity through Genetic Alteration of Adipose Tissue Lipid-Binding Proteins

    Directory of Open Access Journals (Sweden)

    Khanichi N. Charles

    2017-10-01

    Full Text Available Summary: Deterioration of metabolic health is a hallmark of aging and generally assumed to be detrimental to longevity. Exposure to a high-calorie diet impairs metabolism and accelerates aging; conversely, calorie restriction (CR prevents age-related metabolic diseases and extends lifespan. However, it is unclear whether preservation of metabolic health is sufficient to extend lifespan. We utilized a genetic mouse model lacking Fabp4/5 that confers protection against metabolic diseases and shares molecular and lipidomic features with CR to address this question. Fabp-deficient mice exhibit extended metabolic healthspan, with protection against insulin resistance and glucose intolerance, inflammation, deterioration of adipose tissue integrity, and fatty liver disease. Surprisingly, however, Fabp-deficient mice did not exhibit any extension of lifespan. These data indicate that extension of metabolic healthspan in the absence of CR can be uncoupled from lifespan, indicating the potential for independent drivers of these pathways, at least in laboratory mice. : Deterioration of metabolic health is a hallmark of aging and generally thought to be detrimental to longevity. Charles et al. utilize FABP-deficient mice as a model to demonstrate that the preservation of metabolic health in this model persists throughout life, even under metabolic stress, but does not increase longevity. Keywords: fatty acid binding protein, aging, calorie restriction, metabolic health, inflammation, metaflammation, diabetes, obesity, de novo lipogenesis

  5. Combined M-FISH and CGH analysis allows comprehensive description of genetic alterations in neuroblastoma cell lines.

    Science.gov (United States)

    Van Roy, N; Van Limbergen, H; Vandesompele, J; Van Gele, M; Poppe, B; Salwen, H; Laureys, G; Manoel, N; De Paepe, A; Speleman, F

    2001-10-01

    Cancer cell lines are essential gene discovery tools and have often served as models in genetic and functional studies of particular tumor types. One of the future challenges is comparison and interpretation of gene expression data with the available knowledge on the genomic abnormalities in these cell lines. In this context, accurate description of these genomic abnormalities is required. Here, we show that a combination of M-FISH with banding analysis, standard FISH, and CGH allowed a detailed description of the genetic alterations in 16 neuroblastoma cell lines. In total, 14 cryptic chromosome rearrangements were detected, including a balanced t(2;4)(p24.3;q34.3) translocation in cell line NBL-S, with the 2p24 breakpoint located at about 40 kb from MYCN. The chromosomal origin of 22 marker chromosomes and 41 cytogenetically undefined translocated segments was determined. Chromosome arm 2 short arm translocations were observed in six cell lines (38%) with and five (31%) without MYCN amplification, leading to partial chromosome arm 2p gain in all but one cell line and loss of material in the various partner chromosomes, including 1p and 11q. These 2p gains were often masked in the GGH profiles due to MYCN amplification. The commonly overrepresented region was chromosome segment 2pter-2p22, which contains the MYCN gene, and five out of eleven 2p breakpoints clustered to the interface of chromosome bands 2p16 and 2p21. In neuroblastoma cell line SJNB-12, with double minutes (dmins) but no MYCN amplification, the dmins were shown to be derived from 16q22-q23 sequences. The ATBF1 gene, an AT-binding transcription factor involved in normal neurogenesis and located at 16q22.2, was shown to be present in the amplicon. This is the first report describing the possible implication of ATBF1 in neuroblastoma cells. We conclude that a combined approach of M-FISH, cytogenetics, and CGH allowed a more complete and accurate description of the genetic alterations occurring in the

  6. Research on prediction of agricultural machinery total power based on grey model optimized by genetic algorithm

    Science.gov (United States)

    Xie, Yan; Li, Mu; Zhou, Jin; Zheng, Chang-zheng

    2009-07-01

    Agricultural machinery total power is an important index to reflex and evaluate the level of agricultural mechanization. It is the power source of agricultural production, and is the main factors to enhance the comprehensive agricultural production capacity expand production scale and increase the income of the farmers. Its demand is affected by natural, economic, technological and social and other "grey" factors. Therefore, grey system theory can be used to analyze the development of agricultural machinery total power. A method based on genetic algorithm optimizing grey modeling process is introduced in this paper. This method makes full use of the advantages of the grey prediction model and characteristics of genetic algorithm to find global optimization. So the prediction model is more accurate. According to data from a province, the GM (1, 1) model for predicting agricultural machinery total power was given based on the grey system theories and genetic algorithm. The result indicates that the model can be used as agricultural machinery total power an effective tool for prediction.

  7. GRECOS project. The use of genetics to predict the vascular recurrence after stroke

    Science.gov (United States)

    Fernández-Cadenas, Israel; Mendióroz, Maite; Giralt, Dolors; Nafria, Cristina; Garcia, Elena; Carrera, Caty; Gallego-Fabrega, Cristina; Domingues-Montanari, Sophie; Delgado, Pilar; Ribó, Marc; Castellanos, Mar; Martínez, Sergi; Freijo, Mari Mar; Jiménez-Conde, Jordi; Rubiera, Marta; Alvarez-Sabín, José; Molina, Carlos A.; Font, Maria Angels; Olivares, Marta Grau; Palomeras, Ernest; de la Ossa, Natalia Perez; Martinez-Zabaleta, Maite; Masjuan, Jaime; Moniche, Francisco; Canovas, David; Piñana, Carlos; Purroy, Francisco; Cocho, Dolores; Navas, Inma; Tejero, Carlos; Aymerich, Nuria; Cullell, Natalia; Muiño, Elena; Serena, Joaquín; Rubio, Francisco; Davalos, Antoni; Roquer, Jaume; Arenillas, Juan Francisco; Martí-Fábregas, Joan; Keene, Keith; Chen, Wei-Min; Worrall, Bradford; Sale, Michele; Arboix, Adrià; Krupinski, Jerzy; Montaner, Joan

    2017-01-01

    Background and Purpose Vascular recurrence occurs in 11% of patients during the first year after ischemic stroke (IS) or transient ischemic attack (TIA). Clinical scores do not predict the whole vascular recurrence risk, therefore we aimed to find genetic variants associated with recurrence that might improve the clinical predictive models in IS. Methods We analyzed 256 polymorphisms from 115 candidate genes in three patient cohorts comprising 4,482 IS or TIA patients. The discovery cohort was prospectively recruited and included 1,494 patients, 6.2% of them developed a new IS during the first year of follow-up. Replication analysis was performed in 2,988 patients using SNPlex or HumanOmni1-Quad technology. We generated a predictive model using Cox regression (GRECOS score), and generated risk groups using a classification tree method. Results The analyses revealed that rs1800801 in the MGP gene (HR: 1.33, p= 9×10−03), a gene related to artery calcification, was associated with new IS during the first year of follow-up. This polymorphism was replicated in a Spanish cohort (n=1.305), however it was not significantly associated in a North American cohort (n=1.683). The GRECOS score predicted new IS (p= 3.2×10−09) and could classify patients, from low risk of stroke recurrence (1.9%) to high risk (12.6%). Moreover, the addition of genetic risk factors to the GRECOS score improves the prediction compared to previous SPI-II score (p=0.03). Conclusions The use of genetics could be useful to estimate vascular recurrence risk after IS. Genetic variability in the MGP gene was associated with vascular recurrence in the Spanish population. PMID:28411264

  8. PIK3CA Mutation in Colorectal Cancer: Relationship with Genetic and Epigenetic Alterations

    Directory of Open Access Journals (Sweden)

    Katsuhiko Nosho

    2008-06-01

    Full Text Available Somatic PIK3CA mutations are often present in colorectal cancer. Mutant PIK3CA activates AKT signaling, which up-regulates fatty acid synthase (FASN. Microsatellite instability (MSI and CpG island methylator phenotype (CIMP are important molecular classifiers in colorectal cancer. However, the relationship between PIK3CA mutation, MSI and CIMP remains uncertain. Using Pyrosequencing technology, we detected PIK3CA mutations in 91 (15% of 590 population-based colorectal cancers. To determine CIMP status, we quantified DNA methylation in eight CIMP-specific promoters [CACNA1G, CDKN2A (p16, CRABP1, IGF2, MLH1, NEUROG1, RUNX3, and SOCS1] by real-time polymerase chain reaction (MethyLight. PIK3CA mutation was significantly associated with mucinous tumors [P = .0002; odds ratio (OR = 2.44], KRAS mutation (P < .0001; OR = 2.68, CIMP-high (P = .03; OR = 2.08, phospho–ribosomal protein S6 expression (P = .002; OR = 2.19, and FASN expression (P = .02; OR = 1.85 and inversely with p53 expression (P = .01; OR = 0.54 and β-catenin (CTNNB1 alteration (P = .004; OR = 0.43. In addition, PIK3CA G-to-A mutations were associated with MGMT loss (P = .001; OR = 3.24 but not with MGMT promoter methylation. In conclusion, PIK3CA mutation is significantly associated with other key molecular events in colorectal cancer, and MGMT loss likely contributes to the development of PIK3CA G>A mutation. In addition, Pyrosequencing is useful in detecting PIK3CA mutation in archival paraffin tumor tissue. PIK3CA mutational data further emphasize heterogeneity of colorectal cancer at the molecular level.

  9. Ontogeny of mouse vestibulo-ocular reflex following genetic or environmental alteration of gravity sensing.

    Directory of Open Access Journals (Sweden)

    Mathieu Beraneck

    Full Text Available The vestibular organs consist of complementary sensors: the semicircular canals detect rotations while the otoliths detect linear accelerations, including the constant pull of gravity. Several fundamental questions remain on how the vestibular system would develop and/or adapt to prolonged changes in gravity such as during long-term space journey. How do vestibular reflexes develop if the appropriate assembly of otoliths and semi-circular canals is perturbed? The aim of present work was to evaluate the role of gravity sensing during ontogeny of the vestibular system. In otoconia-deficient mice (ied, gravity cannot be sensed and therefore maculo-ocular reflexes (MOR were absent. While canals-related reflexes were present, the ied deficit also led to the abnormal spatial tuning of the horizontal angular canal-related VOR. To identify putative otolith-related critical periods, normal C57Bl/6J mice were subjected to 2G hypergravity by chronic centrifugation during different periods of development or adulthood (Adult-HG and compared to non-centrifuged (control C57Bl/6J mice. Mice exposed to hypergravity during development had completely normal vestibulo-ocular reflexes 6 months after end of centrifugation. Adult-HG mice all displayed major abnormalities in maculo-ocular reflexe one month after return to normal gravity. During the next 5 months, adaptation to normal gravity occurred in half of the individuals. In summary, genetic suppression of gravity sensing indicated that otolith-related signals might be necessary to ensure proper functioning of canal-related vestibular reflexes. On the other hand, exposure to hypergravity during development was not sufficient to modify durably motor behaviour. Hence, 2G centrifugation during development revealed no otolith-specific critical period.

  10. Direct-to-consumer genetic testing for predicting sports performance and talent identification: Consensus statement.

    Science.gov (United States)

    Webborn, Nick; Williams, Alun; McNamee, Mike; Bouchard, Claude; Pitsiladis, Yannis; Ahmetov, Ildus; Ashley, Euan; Byrne, Nuala; Camporesi, Silvia; Collins, Malcolm; Dijkstra, Paul; Eynon, Nir; Fuku, Noriyuki; Garton, Fleur C; Hoppe, Nils; Holm, Søren; Kaye, Jane; Klissouras, Vassilis; Lucia, Alejandro; Maase, Kamiel; Moran, Colin; North, Kathryn N; Pigozzi, Fabio; Wang, Guan

    2015-12-01

    The general consensus among sport and exercise genetics researchers is that genetic tests have no role to play in talent identification or the individualised prescription of training to maximise performance. Despite the lack of evidence, recent years have witnessed the rise of an emerging market of direct-to-consumer marketing (DTC) tests that claim to be able to identify children's athletic talents. Targeted consumers include mainly coaches and parents. There is concern among the scientific community that the current level of knowledge is being misrepresented for commercial purposes. There remains a lack of universally accepted guidelines and legislation for DTC testing in relation to all forms of genetic testing and not just for talent identification. There is concern over the lack of clarity of information over which specific genes or variants are being tested and the almost universal lack of appropriate genetic counselling for the interpretation of the genetic data to consumers. Furthermore independent studies have identified issues relating to quality control by DTC laboratories with different results being reported from samples from the same individual. Consequently, in the current state of knowledge, no child or young athlete should be exposed to DTC genetic testing to define or alter training or for talent identification aimed at selecting gifted children or adolescents. Large scale collaborative projects, may help to develop a stronger scientific foundation on these issues in the future. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

  11. A population-based survey in Australia of men's and women's perceptions of genetic risk and predictive genetic testing and implications for primary care.

    Science.gov (United States)

    Taylor, S

    2011-01-01

    Community attitudes research regarding genetic issues is important when contemplating the potential value and utilisation of predictive testing for common diseases in mainstream health services. This article aims to report population-based attitudes and discuss their relevance to integrating genetic services in primary health contexts. Men's and women's attitudes were investigated via population-based omnibus telephone survey in Queensland, Australia. Randomly selected adults (n = 1,230) with a mean age of 48.8 years were interviewed regarding perceptions of genetic determinants of health; benefits of genetic testing that predict 'certain' versus 'probable' future illness; and concern, if any, regarding potential misuse of genetic test information. Most (75%) respondents believed genetic factors significantly influenced health status; 85% regarded genetic testing positively although attitudes varied with age. Risk-based information was less valued than certainty-based information, but women valued risk information significantly more highly than men. Respondents reported 'concern' (44%) and 'no concern' (47%) regarding potential misuse of genetic information. This study contributes important population-based data as most research has involved selected individuals closely impacted by genetic disorders. While community attitudes were positive regarding genetic testing, genetic literacy is important to establish. The nature of gender differences regarding risk perception merits further study and has policy and service implications. Community concern about potential genetic discrimination must be addressed if health benefits of testing are to be maximised. Larger questions remain in scientific, policy, service delivery, and professional practice domains before predictive testing for common disorders is efficacious in mainstream health care. Copyright © 2011 S. Karger AG, Basel.

  12. How Complex, Probable, and Predictable is Genetically Driven Red Queen Chaos?

    Science.gov (United States)

    Duarte, Jorge; Rodrigues, Carla; Januário, Cristina; Martins, Nuno; Sardanyés, Josep

    2015-12-01

    Coevolution between two antagonistic species has been widely studied theoretically for both ecologically- and genetically-driven Red Queen dynamics. A typical outcome of these systems is an oscillatory behavior causing an endless series of one species adaptation and others counter-adaptation. More recently, a mathematical model combining a three-species food chain system with an adaptive dynamics approach revealed genetically driven chaotic Red Queen coevolution. In the present article, we analyze this mathematical model mainly focusing on the impact of species rates of evolution (mutation rates) in the dynamics. Firstly, we analytically proof the boundedness of the trajectories of the chaotic attractor. The complexity of the coupling between the dynamical variables is quantified using observability indices. By using symbolic dynamics theory, we quantify the complexity of genetically driven Red Queen chaos computing the topological entropy of existing one-dimensional iterated maps using Markov partitions. Co-dimensional two bifurcation diagrams are also built from the period ordering of the orbits of the maps. Then, we study the predictability of the Red Queen chaos, found in narrow regions of mutation rates. To extend the previous analyses, we also computed the likeliness of finding chaos in a given region of the parameter space varying other model parameters simultaneously. Such analyses allowed us to compute a mean predictability measure for the system in the explored region of the parameter space. We found that genetically driven Red Queen chaos, although being restricted to small regions of the analyzed parameter space, might be highly unpredictable.

  13. Predictive Control of Hydronic Floor Heating Systems using Neural Networks and Genetic Algorithms

    DEFF Research Database (Denmark)

    Vinther, Kasper; Green, Torben; Østergaard, Søren

    2017-01-01

    This paper presents the use a neural network and a micro genetic algorithm to optimize future set-points in existing hydronic floor heating systems for improved energy efficiency. The neural network can be trained to predict the impact of changes in set-points on future room temperatures. Additio...... space is not guaranteed. Evaluation of the performance of multiple neural networks is performed, using different levels of information, and optimization results are presented on a detailed house simulation model....

  14. Persistency of Prediction Accuracy and Genetic Gain in Synthetic Populations Under Recurrent Genomic Selection.

    Science.gov (United States)

    Müller, Dominik; Schopp, Pascal; Melchinger, Albrecht E

    2017-03-10

    Recurrent selection (RS) has been used in plant breeding to successively improve synthetic and other multiparental populations. Synthetics are generated from a limited number of parents [Formula: see text] but little is known about how [Formula: see text] affects genomic selection (GS) in RS, especially the persistency of prediction accuracy ([Formula: see text]) and genetic gain. Synthetics were simulated by intermating [Formula: see text]= 2-32 parent lines from an ancestral population with short- or long-range linkage disequilibrium ([Formula: see text]) and subjected to multiple cycles of GS. We determined [Formula: see text] and genetic gain across 30 cycles for different training set ( TS ) sizes, marker densities, and generations of recombination before model training. Contributions to [Formula: see text] and genetic gain from pedigree relationships, as well as from cosegregation and [Formula: see text] between QTL and markers, were analyzed via four scenarios differing in (i) the relatedness between TS and selection candidates and (ii) whether selection was based on markers or pedigree records. Persistency of [Formula: see text] was high for small [Formula: see text] where predominantly cosegregation contributed to [Formula: see text], but also for large [Formula: see text] where [Formula: see text] replaced cosegregation as the dominant information source. Together with increasing genetic variance, this compensation resulted in relatively constant long- and short-term genetic gain for increasing [Formula: see text] > 4, given long-range LD A in the ancestral population. Although our scenarios suggest that information from pedigree relationships contributed to [Formula: see text] for only very few generations in GS, we expect a longer contribution than in pedigree BLUP, because capturing Mendelian sampling by markers reduces selective pressure on pedigree relationships. Larger TS size ([Formula: see text]) and higher marker density improved persistency of

  15. Persistency of Prediction Accuracy and Genetic Gain in Synthetic Populations Under Recurrent Genomic Selection

    Directory of Open Access Journals (Sweden)

    Dominik Müller

    2017-03-01

    Full Text Available Recurrent selection (RS has been used in plant breeding to successively improve synthetic and other multiparental populations. Synthetics are generated from a limited number of parents ( Np , but little is known about how Np affects genomic selection (GS in RS, especially the persistency of prediction accuracy (rg , g ^ and genetic gain. Synthetics were simulated by intermating Np= 2–32 parent lines from an ancestral population with short- or long-range linkage disequilibrium (LDA and subjected to multiple cycles of GS. We determined rg , g ^ and genetic gain across 30 cycles for different training set (TS sizes, marker densities, and generations of recombination before model training. Contributions to rg , g ^ and genetic gain from pedigree relationships, as well as from cosegregation and LDA between QTL and markers, were analyzed via four scenarios differing in (i the relatedness between TS and selection candidates and (ii whether selection was based on markers or pedigree records. Persistency of rg , g ^ was high for small Np , where predominantly cosegregation contributed to rg , g ^ , but also for large Np , where LDA replaced cosegregation as the dominant information source. Together with increasing genetic variance, this compensation resulted in relatively constant long- and short-term genetic gain for increasing Np > 4, given long-range LDA in the ancestral population. Although our scenarios suggest that information from pedigree relationships contributed to rg , g ^ for only very few generations in GS, we expect a longer contribution than in pedigree BLUP, because capturing Mendelian sampling by markers reduces selective pressure on pedigree relationships. Larger TS size (NTS and higher marker density improved persistency of rg , g ^ and hence genetic gain, but additional recombinations could not increase genetic gain.

  16. [Willingness of Students of Economics to Pay for Predictive Oncological Genetic Testing - An Empirical Analysis].

    Science.gov (United States)

    Siol, V; Lange, A; Prenzler, A; Neubauer, S; Frank, M

    2017-05-01

    Objectives: The present study aims to investigate the interest of young adults in predictive oncological genetic testing and their willingness to pay for such a test. Furthermore, major determinants of the 2 variables of interest were identified. Methods: 348 students of economics from the Leibniz University of Hanover were queried in July 2013 using an extensive questionnaire. Among other things, the participants were asked if they are interested in information about the probability to develop cancer in the future and their willingness to pay for such information. Data were analysed using descriptive statistics and ordinal probit regressions. Additionally marginal effects were calculated. Results: About 50% of the students were interested in predictive oncological genetic testing and were willing to pay for the test. Moreover, the participants who were willing to pay for the test partly attach high monetary values to the information that could so be obtained. The study shows that the interest of the students and their willingness to pay were primarily influenced by individual attitudes and perceptions. Conclusions: The study proves that young adults were interested in predictive genetic testing and appreciate information about their probability of develop cancer someday. © Georg Thieme Verlag KG Stuttgart · New York.

  17. Semi-automatic classification of skeletal morphology in genetically altered mice using flat-panel volume computed tomography.

    Directory of Open Access Journals (Sweden)

    Christian Dullin

    2007-07-01

    Full Text Available Rapid progress in exploring the human and mouse genome has resulted in the generation of a multitude of mouse models to study gene functions in their biological context. However, effective screening methods that allow rapid noninvasive phenotyping of transgenic and knockout mice are still lacking. To identify murine models with bone alterations in vivo, we used flat-panel volume computed tomography (fpVCT for high-resolution 3-D imaging and developed an algorithm with a computational intelligence system. First, we tested the accuracy and reliability of this approach by imaging discoidin domain receptor 2- (DDR2- deficient mice, which display distinct skull abnormalities as shown by comparative landmark-based analysis. High-contrast fpVCT data of the skull with 200 microm isotropic resolution and 8-s scan time allowed segmentation and computation of significant shape features as well as visualization of morphological differences. The application of a trained artificial neuronal network to these datasets permitted a semi-automatic and highly accurate phenotype classification of DDR2-deficient compared to C57BL/6 wild-type mice. Even heterozygous DDR2 mice with only subtle phenotypic alterations were correctly determined by fpVCT imaging and identified as a new class. In addition, we successfully applied the algorithm to classify knockout mice lacking the DDR1 gene with no apparent skull deformities. Thus, this new method seems to be a potential tool to identify novel mouse phenotypes with skull changes from transgenic and knockout mice on the basis of random mutagenesis as well as from genetic models. However for this purpose, new neuronal networks have to be created and trained. In summary, the combination of fpVCT images with artificial neuronal networks provides a reliable, novel method for rapid, cost-effective, and noninvasive primary screening tool to detect skeletal phenotypes in mice.

  18. Evaluation of genetic alteration induced by radon gas using the micronucleus test (Tradescantia sp. clone KU-20)

    International Nuclear Information System (INIS)

    Bruschi, Armando L.; Azevedo, Heliana de; Macacini, Jose F.; Roque, Claudio V.

    2011-01-01

    The first observations over the existence of radon gas (Rn), initially known as 'thorium emanation', were carried out between the end of 19 th and beginning of 20 th centuries. A result of uranium-238 (U 238 ) radioactive decay, radon is a tasteless, odorless and colorless gas under room temperature, with a 3.825-day half life and particle α emission in its decay, and as final product of its disintegration, the stable lead-206 isotope (Pb 206 ). Being it is the gas with the highest density known, closed and poor ventilated environments are favorable to its accumulation, with its inhalation being the highest health risk. The use of vegetal bioindicators has shown to be excellent on the monitoring of air quality and on mutagenic potential of various pollutants contained in the atmosphere. Within this context, the objective of this study was to evaluate the micronucleus test application potential utilizing the Tradescantia sp. clone KU-20, in order to evaluate genetic alterations induced by radon gas. Stems of Tradescantia sp. clone KU-20, previously immerse in Hoagland solution, were introduced in a radon detection equipment's calibration chamber (Alphaguard), containing radium salt. Afterwards, the accommodated stems were exposed to radon gas (the average radon concentration was 7.639 KBq/m3) for 24 hours. The results demonstrated an increase on micronucleus formation (39.23 + 2.143 MCN/100 tetrads) in stems exposed in relation to the negative control (18.00 + 1.396 MCN/100 tetrads). The difference between the values indicated a significant increase on micronucleus frequency in the inflorescences subjected to radon gas. The presented results demonstrated the micronucleus test application potential using Tradescantia clone KU-20 to evaluate genetic effects induced by radon gas. (author)

  19. Genetic Alterations in Essential Thrombocythemia Progression to Acute Myeloid Leukemia: A Case Series and Review of the Literature

    Directory of Open Access Journals (Sweden)

    Jackline P. Ayres-Silva

    2018-02-01

    Full Text Available The genetic events associated with transformation of myeloproliferative neoplasms (MPNs to secondary acute myeloid leukemia (sAML, particularly in the subgroup of essential thrombocythemia (ET patients, remain incompletely understood. Deep studies using high-throughput methods might lead to a better understanding of genetic landscape of ET patients who transformed to sAML. We performed array-based comparative genomic hybridization (aCGH and whole exome sequencing (WES to analyze paired samples from ET and sAML phases. We investigated five patients with previous history of MPN, which four had initial diagnosis of ET (one case harboring JAK2 p.Val617Phe and the remaining three CALR type II p.Lys385fs*47, and one was diagnosed with MPN/myelodysplastic syndrome with thrombocytosis (SF3B1 p.Lys700Glu. All were homogeneously treated with hydroxyurea, but subsequently transformed to sAML (mean time of 6 years/median of 4 years to transformation. Two of them have chromosomal abnormalities, and both acquire 2p gain and 5q deletion at sAML stage. The molecular mechanisms associated with leukemic progression in MPN patients are not clear. Our WES data showed TP53 alterations recurrently observed as mutations (missense and frameshift and monoallelic loss. On the other hand, aCGH showed novel chromosome abnormalities (+2p and del5q potentially associated with disease progression. The results reported here add valuable information to the still fragmented molecular basis of ET to sAML evolution. Further studies are necessary to identify minimal deleted/amplified region and genes relevant to sAML transformation.

  20. Genetic diversity and trait genomic prediction in a pea diversity panel.

    Science.gov (United States)

    Burstin, Judith; Salloignon, Pauline; Chabert-Martinello, Marianne; Magnin-Robert, Jean-Bernard; Siol, Mathieu; Jacquin, Françoise; Chauveau, Aurélie; Pont, Caroline; Aubert, Grégoire; Delaitre, Catherine; Truntzer, Caroline; Duc, Gérard

    2015-02-21

    Pea (Pisum sativum L.), a major pulse crop grown for its protein-rich seeds, is an important component of agroecological cropping systems in diverse regions of the world. New breeding challenges imposed by global climate change and new regulations urge pea breeders to undertake more efficient methods of selection and better take advantage of the large genetic diversity present in the Pisum sativum genepool. Diversity studies conducted so far in pea used Simple Sequence Repeat (SSR) and Retrotransposon Based Insertion Polymorphism (RBIP) markers. Recently, SNP marker panels have been developed that will be useful for genetic diversity assessment and marker-assisted selection. A collection of diverse pea accessions, including landraces and cultivars of garden, field or fodder peas as well as wild peas was characterised at the molecular level using newly developed SNP markers, as well as SSR markers and RBIP markers. The three types of markers were used to describe the structure of the collection and revealed different pictures of the genetic diversity among the collection. SSR showed the fastest rate of evolution and RBIP the slowest rate of evolution, pointing to their contrasted mode of evolution. SNP markers were then used to predict phenotypes -the date of flowering (BegFlo), the number of seeds per plant (Nseed) and thousand seed weight (TSW)- that were recorded for the collection. Different statistical methods were tested including the LASSO (Least Absolute Shrinkage ans Selection Operator), PLS (Partial Least Squares), SPLS (Sparse Partial Least Squares), Bayes A, Bayes B and GBLUP (Genomic Best Linear Unbiased Prediction) methods and the structure of the collection was taken into account in the prediction. Despite a limited number of 331 markers used for prediction, TSW was reliably predicted. The development of marker assisted selection has not reached its full potential in pea until now. This paper shows that the high-throughput SNP arrays that are being

  1. A New Model for Predicting Acute Mucosal Toxicity in Head-and-Neck Cancer Patients Undergoing Radiotherapy With Altered Schedules

    International Nuclear Information System (INIS)

    Strigari, Lidia; Pedicini, Piernicola; D’Andrea, Marco; Pinnarò, Paola; Marucci, Laura; Giordano, Carolina; Benassi, Marcello

    2012-01-01

    Purpose: One of the worst radiation-induced acute effects in treating head-and-neck (HN) cancer is grade 3 or higher acute (oral and pharyngeal) mucosal toxicity (AMT), caused by the killing/depletion of mucosa cells. Here we aim to testing a predictive model of the AMT in HN cancer patients receiving different radiotherapy schedules. Methods and Materials: Various radiotherapeutic schedules have been reviewed and classified as tolerable or intolerable based on AMT severity. A modified normal tissue complication probability (NTCP) model has been investigated to describe AMT data in radiotherapy regimens, both conventional and altered in dose and overall treatment time (OTT). We tested the hypothesis that such a model could also be applied to identify intolerable treatment and to predict AMT. This AMT NTCP model has been compared with other published predictive models to identify schedules that are either tolerable or intolerable. The area under the curve (AUC) was calculated for all models, assuming treatment tolerance as the gold standard. The correlation between AMT and the predicted toxicity rate was assessed by a Pearson correlation test. Results: The AMT NTCP model was able to distinguish between acceptable and intolerable schedules among the data available for the study (AUC = 0.84, 95% confidence interval = 0.75-0.92). In the equivalent dose at 2 Gy/fraction (EQD2) vs OTT space, the proposed model shows a trend similar to that of models proposed by other authors, but was superior in detecting some intolerable schedules. Moreover, it was able to predict the incidence of ≥G3 AMT. Conclusion: The proposed model is able to predict ≥G3 AMT after HN cancer radiotherapy, and could be useful for designing altered/hypofractionated schedules to reduce the incidence of AMT.

  2. Assessment of genetic and nongenetic interactions for the prediction of depressive symptomatology: an analysis of the Wisconsin Longitudinal Study using machine learning algorithms.

    Science.gov (United States)

    Roetker, Nicholas S; Page, C David; Yonker, James A; Chang, Vicky; Roan, Carol L; Herd, Pamela; Hauser, Taissa S; Hauser, Robert M; Atwood, Craig S

    2013-10-01

    We examined depression within a multidimensional framework consisting of genetic, environmental, and sociobehavioral factors and, using machine learning algorithms, explored interactions among these factors that might better explain the etiology of depressive symptoms. We measured current depressive symptoms using the Center for Epidemiologic Studies Depression Scale (n = 6378 participants in the Wisconsin Longitudinal Study). Genetic factors were 78 single nucleotide polymorphisms (SNPs); environmental factors-13 stressful life events (SLEs), plus a composite proportion of SLEs index; and sociobehavioral factors-18 personality, intelligence, and other health or behavioral measures. We performed traditional SNP associations via logistic regression likelihood ratio testing and explored interactions with support vector machines and Bayesian networks. After correction for multiple testing, we found no significant single genotypic associations with depressive symptoms. Machine learning algorithms showed no evidence of interactions. Naïve Bayes produced the best models in both subsets and included only environmental and sociobehavioral factors. We found no single or interactive associations with genetic factors and depressive symptoms. Various environmental and sociobehavioral factors were more predictive of depressive symptoms, yet their impacts were independent of one another. A genome-wide analysis of genetic alterations using machine learning methodologies will provide a framework for identifying genetic-environmental-sociobehavioral interactions in depressive symptoms.

  3. ["Screening" in special situations. Assessing predictive genetic screening for hereditary breast and colorectal cancer].

    Science.gov (United States)

    Jonas, Susanna; Wild, Claudia; Schamberger, Chantal

    2003-02-01

    The aim of this health technology assessment was to analyse the current scientific and genetic counselling on predictive genetic testing for hereditary breast and colorectal cancer. Predictive genetic testing will be available for several common diseases in the future and questions related to financial issues and quality standards will be raised. This report is based on a systematic/nonsystematic literature search in several databases (e.g. EmBase, Medline, Cochrane Library) and on a specific health technology assessment report (CCOHTA) and review (American Gastroenterological Ass.), respectively. Laboratory test methods, early detection methods and the benefit from prophylactic interventions were analysed and social consequences interpreted. Breast and colorectal cancer are counted among the most frequently cancer diseases. Most of them are based on random accumulation of risk factors, 5-10% show a familial determination. A hereditary modified gene is responsible for the increased cancer risk. In these families, high tumour frequency, young age at diagnosis and multiple primary tumours are remarkable. GENETIC DIAGNOSIS: Sequence analysis is the gold standard. Denaturing high performance liquid chromatography is a quick alternative method. The identification of the responsible gene defect in an affected family member is important. If the test result is positive there is an uncertainty whether the disease will develop or not, when and in which degree, which is founded in the geno-/phenotype correlation. The individual risk estimation is based upon empirical evidence. The test results affect the whole family. Currently, primary prevention is possible for familial adenomatous polyposis (celecoxib, prophylactic colectomy) and for hereditary mamma carcinoma (prophylactic mastectomy). The so-called preventive medical check-ups are early detection examinations. The evidence about early detection methods for colorectal cancer is better than for breast cancer. Prophylactic

  4. Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis.

    Science.gov (United States)

    Sieberts, Solveig K; Zhu, Fan; García-García, Javier; Stahl, Eli; Pratap, Abhishek; Pandey, Gaurav; Pappas, Dimitrios; Aguilar, Daniel; Anton, Bernat; Bonet, Jaume; Eksi, Ridvan; Fornés, Oriol; Guney, Emre; Li, Hongdong; Marín, Manuel Alejandro; Panwar, Bharat; Planas-Iglesias, Joan; Poglayen, Daniel; Cui, Jing; Falcao, Andre O; Suver, Christine; Hoff, Bruce; Balagurusamy, Venkat S K; Dillenberger, Donna; Neto, Elias Chaibub; Norman, Thea; Aittokallio, Tero; Ammad-Ud-Din, Muhammad; Azencott, Chloe-Agathe; Bellón, Víctor; Boeva, Valentina; Bunte, Kerstin; Chheda, Himanshu; Cheng, Lu; Corander, Jukka; Dumontier, Michel; Goldenberg, Anna; Gopalacharyulu, Peddinti; Hajiloo, Mohsen; Hidru, Daniel; Jaiswal, Alok; Kaski, Samuel; Khalfaoui, Beyrem; Khan, Suleiman Ali; Kramer, Eric R; Marttinen, Pekka; Mezlini, Aziz M; Molparia, Bhuvan; Pirinen, Matti; Saarela, Janna; Samwald, Matthias; Stoven, Véronique; Tang, Hao; Tang, Jing; Torkamani, Ali; Vert, Jean-Phillipe; Wang, Bo; Wang, Tao; Wennerberg, Krister; Wineinger, Nathan E; Xiao, Guanghua; Xie, Yang; Yeung, Rae; Zhan, Xiaowei; Zhao, Cheng; Greenberg, Jeff; Kremer, Joel; Michaud, Kaleb; Barton, Anne; Coenen, Marieke; Mariette, Xavier; Miceli, Corinne; Shadick, Nancy; Weinblatt, Michael; de Vries, Niek; Tak, Paul P; Gerlag, Danielle; Huizinga, Tom W J; Kurreeman, Fina; Allaart, Cornelia F; Louis Bridges, S; Criswell, Lindsey; Moreland, Larry; Klareskog, Lars; Saevarsdottir, Saedis; Padyukov, Leonid; Gregersen, Peter K; Friend, Stephen; Plenge, Robert; Stolovitzky, Gustavo; Oliva, Baldo; Guan, Yuanfang; Mangravite, Lara M; Bridges, S Louis; Criswell, Lindsey; Moreland, Larry; Klareskog, Lars; Saevarsdottir, Saedis; Padyukov, Leonid; Gregersen, Peter K; Friend, Stephen; Plenge, Robert; Stolovitzky, Gustavo; Oliva, Baldo; Guan, Yuanfang; Mangravite, Lara M

    2016-08-23

    Rheumatoid arthritis (RA) affects millions world-wide. While anti-TNF treatment is widely used to reduce disease progression, treatment fails in ∼one-third of patients. No biomarker currently exists that identifies non-responders before treatment. A rigorous community-based assessment of the utility of SNP data for predicting anti-TNF treatment efficacy in RA patients was performed in the context of a DREAM Challenge (http://www.synapse.org/RA_Challenge). An open challenge framework enabled the comparative evaluation of predictions developed by 73 research groups using the most comprehensive available data and covering a wide range of state-of-the-art modelling methodologies. Despite a significant genetic heritability estimate of treatment non-response trait (h(2)=0.18, P value=0.02), no significant genetic contribution to prediction accuracy is observed. Results formally confirm the expectations of the rheumatology community that SNP information does not significantly improve predictive performance relative to standard clinical traits, thereby justifying a refocusing of future efforts on collection of other data.

  5. Genetically altering the expression of neutral trehalase gene affects conidiospore thermotolerance of the entomopathogenic fungus Metarhizium acridum

    Directory of Open Access Journals (Sweden)

    Peng Guoxiong

    2011-02-01

    Full Text Available Abstract Background The entomopathogenic fungus Metarhizium acridum has been used as an important biocontrol agent instead of insecticides for controlling crop pests throughout the world. However, its virulence varies with environmental factors, especially temperature. Neutral trehalase (Ntl hydrolyzes trehalose, which plays a role in environmental stress response in many organisms, including M. acridum. Demonstration of a relationship between Ntl and thermotolerance or virulence may offer a new strategy for enhancing conidiospore thermotolerance of entomopathogenic fungi through genetic engineering. Results We selected four Ntl over-expression and four Ntl RNA interference (RNAi transformations in which Ntl expression is different. Compared to the wild-type, Ntl mRNA expression was reduced to 35-66% in the RNAi mutants and increased by 2.5-3.5-fold in the over-expression mutants. The RNAi conidiospores exhibited less trehalase activity, accumulated more trehalose, and were much more tolerant of heat stress than the wild-type. The opposite effects were found in conidiospores of over-expression mutants compared to RNAi mutants. Furthermore, virulence was not altered in the two types of mutants compared to the wild type. Conclusions Ntl controlled trehalose accumulation in M. acridum by degrading trehalose, and thus affected conidiospore thermotolerance. These results offer a new strategy for enhancing conidiospore thermotolerance of entomopathogenic fungi without affecting virulence.

  6. Advancement of Phenotype Transformation of Cancer-associated Fibroblasts: 
from Genetic Alterations to Epigenetic Modification

    Directory of Open Access Journals (Sweden)

    Dali CHEN

    2015-02-01

    Full Text Available In the field of human cancer research, even though the vast majority attentions were paid to tumor cells as “the seeds”, the roles of tumor microenvironments as “the soil” are gradually explored in recent years. As a dominant compartment of tumor microenvironments, cancer-associated fibroblasts (CAFs were discovered to correlated with tumorigenesis, tumor progression and prognosis. And the exploration of the mechanisms of CAF phenotype transformation would conducive to the further understand of the CAFs function in human cancers. As we known that CAFs have four main origins, including epithelial cells, endothelial cells, mesenchymal stem cells (MSCs and local mesenchymal cells. However, researchers found that all these origins finally conduct similiar phenotypes from intrinsic to extrinsic ones. Thus, what and how a mechanism can conduct the phenotype transformation of CAFs with different origins? Two viewpoints are proposed to try to answer the quetsion, involving genetic alterations and epigenetic modifications. This review will systematically summarize the advancement of mechanisms of CAF phenotype transformations in the aspect of genentic and epigenetic modifications.

  7. Genetic Deletion of Rheb1 in the Brain Reduces Food Intake and Causes Hypoglycemia with Altered Peripheral Metabolism

    Directory of Open Access Journals (Sweden)

    Wanchun Yang

    2014-01-01

    Full Text Available Excessive food/energy intake is linked to obesity and metabolic disorders, such as diabetes. The hypothalamus in the brain plays a critical role in the control of food intake and peripheral metabolism. The signaling pathways in hypothalamic neurons that regulate food intake and peripheral metabolism need to be better understood for developing pharmacological interventions to manage eating behavior and obesity. Mammalian target of rapamycin (mTOR, a serine/threonine kinase, is a master regulator of cellular metabolism in different cell types. Pharmacological manipulations of mTOR complex 1 (mTORC1 activity in hypothalamic neurons alter food intake and body weight. Our previous study identified Rheb1 (Ras homolog enriched in brain 1 as an essential activator of mTORC1 activity in the brain. Here we examine whether central Rheb1 regulates food intake and peripheral metabolism through mTORC1 signaling. We find that genetic deletion of Rheb1 in the brain causes a reduction in mTORC1 activity and impairs normal food intake. As a result, Rheb1 knockout mice exhibit hypoglycemia and increased lipid mobilization in adipose tissue and ketogenesis in the liver. Our work highlights the importance of central Rheb1 signaling in euglycemia and energy homeostasis in animals.

  8. Hopefulness predicts resilience after hereditary colorectal cancer genetic testing: a prospective outcome trajectories study

    Directory of Open Access Journals (Sweden)

    Chu Annie TW

    2010-06-01

    Full Text Available Abstract Background - Genetic testing for hereditary colorectal cancer (HCRC had significant psychological consequences for test recipients. This prospective longitudinal study investigated the factors that predict psychological resilience in adults undergoing genetic testing for HCRC. Methods - A longitudinal study was carried out from April 2003 to August 2006 on Hong Kong Chinese HCRC family members who were recruited and offered genetic testing by the Hereditary Gastrointestinal Cancer Registry to determine psychological outcomes after genetic testing. Self-completed questionnaires were administered immediately before (pre-disclosure baseline and 2 weeks, 4 months and 1 year after result disclosure. Using validated psychological inventories, the cognitive style of hope was measured at baseline, and the psychological distress of depression and anxiety was measured at all time points. Results - Of the 76 participating subjects, 71 individuals (43 men and 28 women; mean age 38.9 ± 9.2 years from nine FAP and 24 HNPCC families completed the study, including 39 mutated gene carriers. Four patterns of outcome trajectories were created using established norms for the specified outcome measures of depression and anxiety. These included chronic dysfunction (13% and 8.7%, recovery (0% and 4.3%, delayed dysfunction (13% and 15.9% and resilience (76.8% and 66.7%. Two logistic regression analyses were conducted using hope at baseline to predict resilience, with depression and anxiety employed as outcome indicators. Because of the small number of participants, the chronic dysfunction and delayed dysfunction groups were combined into a non-resilient group for comparison with the resilient group in all subsequent analysis. Because of low frequencies, participants exhibiting a recovery trajectory (n = 3 for anxiety and n = 0 for depression were excluded from further analysis. Both regression equations were significant. Baseline hope was a significant

  9. Hopefulness predicts resilience after hereditary colorectal cancer genetic testing: a prospective outcome trajectories study.

    Science.gov (United States)

    Ho, Samuel M Y; Ho, Judy W C; Bonanno, George A; Chu, Annie T W; Chan, Emily M S

    2010-06-11

    Genetic testing for hereditary colorectal cancer (HCRC) had significant psychological consequences for test recipients. This prospective longitudinal study investigated the factors that predict psychological resilience in adults undergoing genetic testing for HCRC. A longitudinal study was carried out from April 2003 to August 2006 on Hong Kong Chinese HCRC family members who were recruited and offered genetic testing by the Hereditary Gastrointestinal Cancer Registry to determine psychological outcomes after genetic testing. Self-completed questionnaires were administered immediately before (pre-disclosure baseline) and 2 weeks, 4 months and 1 year after result disclosure. Using validated psychological inventories, the cognitive style of hope was measured at baseline, and the psychological distress of depression and anxiety was measured at all time points. Of the 76 participating subjects, 71 individuals (43 men and 28 women; mean age 38.9 +/- 9.2 years) from nine FAP and 24 HNPCC families completed the study, including 39 mutated gene carriers. Four patterns of outcome trajectories were created using established norms for the specified outcome measures of depression and anxiety. These included chronic dysfunction (13% and 8.7%), recovery (0% and 4.3%), delayed dysfunction (13% and 15.9%) and resilience (76.8% and 66.7%). Two logistic regression analyses were conducted using hope at baseline to predict resilience, with depression and anxiety employed as outcome indicators. Because of the small number of participants, the chronic dysfunction and delayed dysfunction groups were combined into a non-resilient group for comparison with the resilient group in all subsequent analysis. Because of low frequencies, participants exhibiting a recovery trajectory (n = 3 for anxiety and n = 0 for depression) were excluded from further analysis. Both regression equations were significant. Baseline hope was a significant predictor of a resilience outcome trajectory for depression

  10. An Automated Defect Prediction Framework using Genetic Algorithms: A Validation of Empirical Studies

    Directory of Open Access Journals (Sweden)

    Juan Murillo-Morera

    2016-05-01

    Full Text Available Today, it is common for software projects to collect measurement data through development processes. With these data, defect prediction software can try to estimate the defect proneness of a software module, with the objective of assisting and guiding software practitioners. With timely and accurate defect predictions, practitioners can focus their limited testing resources on higher risk areas. This paper reports the results of three empirical studies that uses an automated genetic defect prediction framework. This framework generates and compares different learning schemes (preprocessing + attribute selection + learning algorithms and selects the best one using a genetic algorithm, with the objective to estimate the defect proneness of a software module. The first empirical study is a performance comparison of our framework with the most important framework of the literature. The second empirical study is a performance and runtime comparison between our framework and an exhaustive framework. The third empirical study is a sensitivity analysis. The last empirical study, is our main contribution in this paper. Performance of the software development defect prediction models (using AUC, Area Under the Curve was validated using NASA-MDP and PROMISE data sets. Seventeen data sets from NASA-MDP (13 and PROMISE (4 projects were analyzed running a NxM-fold cross-validation. A genetic algorithm was used to select the components of the learning schemes automatically, and to assess and report the results. Our results reported similar performance between frameworks. Our framework reported better runtime than exhaustive framework. Finally, we reported the best configuration according to sensitivity analysis.

  11. Multiple-Trait Genomic Selection Methods Increase Genetic Value Prediction Accuracy

    Science.gov (United States)

    Jia, Yi; Jannink, Jean-Luc

    2012-01-01

    Genetic correlations between quantitative traits measured in many breeding programs are pervasive. These correlations indicate that measurements of one trait carry information on other traits. Current single-trait (univariate) genomic selection does not take advantage of this information. Multivariate genomic selection on multiple traits could accomplish this but has been little explored and tested in practical breeding programs. In this study, three multivariate linear models (i.e., GBLUP, BayesA, and BayesCπ) were presented and compared to univariate models using simulated and real quantitative traits controlled by different genetic architectures. We also extended BayesA with fixed hyperparameters to a full hierarchical model that estimated hyperparameters and BayesCπ to impute missing phenotypes. We found that optimal marker-effect variance priors depended on the genetic architecture of the trait so that estimating them was beneficial. We showed that the prediction accuracy for a low-heritability trait could be significantly increased by multivariate genomic selection when a correlated high-heritability trait was available. Further, multiple-trait genomic selection had higher prediction accuracy than single-trait genomic selection when phenotypes are not available on all individuals and traits. Additional factors affecting the performance of multiple-trait genomic selection were explored. PMID:23086217

  12. Applications of population genetics to animal breeding, from wright, fisher and lush to genomic prediction.

    Science.gov (United States)

    Hill, William G

    2014-01-01

    Although animal breeding was practiced long before the science of genetics and the relevant disciplines of population and quantitative genetics were known, breeding programs have mainly relied on simply selecting and mating the best individuals on their own or relatives' performance. This is based on sound quantitative genetic principles, developed and expounded by Lush, who attributed much of his understanding to Wright, and formalized in Fisher's infinitesimal model. Analysis at the level of individual loci and gene frequency distributions has had relatively little impact. Now with access to genomic data, a revolution in which molecular information is being used to enhance response with "genomic selection" is occurring. The predictions of breeding value still utilize multiple loci throughout the genome and, indeed, are largely compatible with additive and specifically infinitesimal model assumptions. I discuss some of the history and genetic issues as applied to the science of livestock improvement, which has had and continues to have major spin-offs into ideas and applications in other areas.

  13. Artificial Neural Network and Genetic Algorithm Hybrid Intelligence for Predicting Thai Stock Price Index Trend

    Directory of Open Access Journals (Sweden)

    Montri Inthachot

    2016-01-01

    Full Text Available This study investigated the use of Artificial Neural Network (ANN and Genetic Algorithm (GA for prediction of Thailand’s SET50 index trend. ANN is a widely accepted machine learning method that uses past data to predict future trend, while GA is an algorithm that can find better subsets of input variables for importing into ANN, hence enabling more accurate prediction by its efficient feature selection. The imported data were chosen technical indicators highly regarded by stock analysts, each represented by 4 input variables that were based on past time spans of 4 different lengths: 3-, 5-, 10-, and 15-day spans before the day of prediction. This import undertaking generated a big set of diverse input variables with an exponentially higher number of possible subsets that GA culled down to a manageable number of more effective ones. SET50 index data of the past 6 years, from 2009 to 2014, were used to evaluate this hybrid intelligence prediction accuracy, and the hybrid’s prediction results were found to be more accurate than those made by a method using only one input variable for one fixed length of past time span.

  14. Artificial Neural Network and Genetic Algorithm Hybrid Intelligence for Predicting Thai Stock Price Index Trend

    Science.gov (United States)

    Boonjing, Veera; Intakosum, Sarun

    2016-01-01

    This study investigated the use of Artificial Neural Network (ANN) and Genetic Algorithm (GA) for prediction of Thailand's SET50 index trend. ANN is a widely accepted machine learning method that uses past data to predict future trend, while GA is an algorithm that can find better subsets of input variables for importing into ANN, hence enabling more accurate prediction by its efficient feature selection. The imported data were chosen technical indicators highly regarded by stock analysts, each represented by 4 input variables that were based on past time spans of 4 different lengths: 3-, 5-, 10-, and 15-day spans before the day of prediction. This import undertaking generated a big set of diverse input variables with an exponentially higher number of possible subsets that GA culled down to a manageable number of more effective ones. SET50 index data of the past 6 years, from 2009 to 2014, were used to evaluate this hybrid intelligence prediction accuracy, and the hybrid's prediction results were found to be more accurate than those made by a method using only one input variable for one fixed length of past time span. PMID:27974883

  15. Predicting the genetic consequences of future climate change: The power of coupling spatial demography, the coalescent, and historical landscape changes.

    Science.gov (United States)

    Brown, Jason L; Weber, Jennifer J; Alvarado-Serrano, Diego F; Hickerson, Michael J; Franks, Steven J; Carnaval, Ana C

    2016-01-01

    Climate change is a widely accepted threat to biodiversity. Species distribution models (SDMs) are used to forecast whether and how species distributions may track these changes. Yet, SDMs generally fail to account for genetic and demographic processes, limiting population-level inferences. We still do not understand how predicted environmental shifts will impact the spatial distribution of genetic diversity within taxa. We propose a novel method that predicts spatially explicit genetic and demographic landscapes of populations under future climatic conditions. We use carefully parameterized SDMs as estimates of the spatial distribution of suitable habitats and landscape dispersal permeability under present-day, past, and future conditions. We use empirical genetic data and approximate Bayesian computation to estimate unknown demographic parameters. Finally, we employ these parameters to simulate realistic and complex models of responses to future environmental shifts. We contrast parameterized models under current and future landscapes to quantify the expected magnitude of change. We implement this framework on neutral genetic data available from Penstemon deustus. Our results predict that future climate change will result in geographically widespread declines in genetic diversity in this species. The extent of reduction will heavily depend on the continuity of population networks and deme sizes. To our knowledge, this is the first study to provide spatially explicit predictions of within-species genetic diversity using climatic, demographic, and genetic data. Our approach accounts for climatic, geographic, and biological complexity. This framework is promising for understanding evolutionary consequences of climate change, and guiding conservation planning. © 2016 Botanical Society of America.

  16. Predicting evolutionary responses when genetic variance and selection covary with the environment: a large-scale Open Access Data approach

    NARCIS (Netherlands)

    Ramakers, J.J.C.; Culina, A.; Visser, M.E.; Gienapp, P.

    2017-01-01

    Additive genetic variance and selection are the key ingredients for evolution. In wild populations, however, predicting evolutionary trajectories is difficult, potentially by an unrecognised underlying environment dependency of both (additive) genetic variance and selection (i.e. G×E and S×E).

  17. Prediction of Aerodynamic Coefficients for Wind Tunnel Data using a Genetic Algorithm Optimized Neural Network

    Science.gov (United States)

    Rajkumar, T.; Aragon, Cecilia; Bardina, Jorge; Britten, Roy

    2002-01-01

    A fast, reliable way of predicting aerodynamic coefficients is produced using a neural network optimized by a genetic algorithm. Basic aerodynamic coefficients (e.g. lift, drag, pitching moment) are modelled as functions of angle of attack and Mach number. The neural network is first trained on a relatively rich set of data from wind tunnel tests of numerical simulations to learn an overall model. Most of the aerodynamic parameters can be well-fitted using polynomial functions. A new set of data, which can be relatively sparse, is then supplied to the network to produce a new model consistent with the previous model and the new data. Because the new model interpolates realistically between the sparse test data points, it is suitable for use in piloted simulations. The genetic algorithm is used to choose a neural network architecture to give best results, avoiding over-and under-fitting of the test data.

  18. Predicting risk in space: Genetic markers for differential vulnerability to sleep restriction

    Science.gov (United States)

    Goel, Namni; Dinges, David F.

    2012-08-01

    Several laboratories have found large, highly reliable individual differences in the magnitude of cognitive performance, fatigue and sleepiness, and sleep homeostatic vulnerability to acute total sleep deprivation and to chronic sleep restriction in healthy adults. Such individual differences in neurobehavioral performance are also observed in space flight as a result of sleep loss. The reasons for these stable phenotypic differential vulnerabilities are unknown: such differences are not yet accounted for by demographic factors, IQ or sleep need, and moreover, psychometric scales do not predict those individuals cognitively vulnerable to sleep loss. The stable, trait-like (phenotypic) inter-individual differences observed in response to sleep loss—with intraclass correlation coefficients accounting for 58-92% of the variance in neurobehavioral measures—point to an underlying genetic component. To this end, we utilized multi-day highly controlled laboratory studies to investigate the role of various common candidate gene variants—each independently—in relation to cumulative neurobehavioral and sleep homeostatic responses to sleep restriction. These data suggest that common genetic variations (polymorphisms) involved in sleep-wake, circadian, and cognitive regulation may serve as markers for prediction of inter-individual differences in sleep homeostatic and neurobehavioral vulnerability to sleep restriction in healthy adults. Identification of genetic predictors of differential vulnerability to sleep restriction—as determined from candidate gene studies—will help identify astronauts most in need of fatigue countermeasures in space flight and inform medical standards for obtaining adequate sleep in space. This review summarizes individual differences in neurobehavioral vulnerability to sleep deprivation and ongoing genetic efforts to identify markers of such differences.

  19. High Interannual Variability in Connectivity and Genetic Pool of a Temperate Clingfish Matches Oceanographic Transport Predictions

    Science.gov (United States)

    Teixeira, Sara; Assis, Jorge; Serrão, Ester A.; Gonçalves, Emanuel J.; Borges, Rita

    2016-01-01

    Adults of most marine benthic and demersal fish are site-attached, with the dispersal of their larval stages ensuring connectivity among populations. In this study we aimed to infer spatial and temporal variation in population connectivity and dispersal of a marine fish species, using genetic tools and comparing these with oceanographic transport. We focused on an intertidal rocky reef fish species, the shore clingfish Lepadogaster lepadogaster, along the southwest Iberian Peninsula, in 2011 and 2012. We predicted high levels of self-recruitment and distinct populations, due to short pelagic larval duration and because all its developmental stages have previously been found near adult habitats. Genetic analyses based on microsatellites countered our prediction and a biophysical dispersal model showed that oceanographic transport was a good explanation for the patterns observed. Adult sub-populations separated by up to 300 km of coastline displayed no genetic differentiation, revealing a single connected population with larvae potentially dispersing long distances over hundreds of km. Despite this, parentage analysis performed on recruits from one focal site within the Marine Park of Arrábida (Portugal), revealed self-recruitment levels of 2.5% and 7.7% in 2011 and 2012, respectively, suggesting that both long- and short-distance dispersal play an important role in the replenishment of these populations. Population differentiation and patterns of dispersal, which were highly variable between years, could be linked to the variability inherent in local oceanographic processes. Overall, our measures of connectivity based on genetic and oceanographic data highlight the relevance of long-distance dispersal in determining the degree of connectivity, even in species with short pelagic larval durations. PMID:27911952

  20. Ab-initio conformational epitope structure prediction using genetic algorithm and SVM for vaccine design.

    Science.gov (United States)

    Moghram, Basem Ameen; Nabil, Emad; Badr, Amr

    2018-01-01

    T-cell epitope structure identification is a significant challenging immunoinformatic problem within epitope-based vaccine design. Epitopes or antigenic peptides are a set of amino acids that bind with the Major Histocompatibility Complex (MHC) molecules. The aim of this process is presented by Antigen Presenting Cells to be inspected by T-cells. MHC-molecule-binding epitopes are responsible for triggering the immune response to antigens. The epitope's three-dimensional (3D) molecular structure (i.e., tertiary structure) reflects its proper function. Therefore, the identification of MHC class-II epitopes structure is a significant step towards epitope-based vaccine design and understanding of the immune system. In this paper, we propose a new technique using a Genetic Algorithm for Predicting the Epitope Structure (GAPES), to predict the structure of MHC class-II epitopes based on their sequence. The proposed Elitist-based genetic algorithm for predicting the epitope's tertiary structure is based on Ab-Initio Empirical Conformational Energy Program for Peptides (ECEPP) Force Field Model. The developed secondary structure prediction technique relies on Ramachandran Plot. We used two alignment algorithms: the ROSS alignment and TM-Score alignment. We applied four different alignment approaches to calculate the similarity scores of the dataset under test. We utilized the support vector machine (SVM) classifier as an evaluation of the prediction performance. The prediction accuracy and the Area Under Receiver Operating Characteristic (ROC) Curve (AUC) were calculated as measures of performance. The calculations are performed on twelve similarity-reduced datasets of the Immune Epitope Data Base (IEDB) and a large dataset of peptide-binding affinities to HLA-DRB1*0101. The results showed that GAPES was reliable and very accurate. We achieved an average prediction accuracy of 93.50% and an average AUC of 0.974 in the IEDB dataset. Also, we achieved an accuracy of 95

  1. Improved feature selection based on genetic algorithms for real time disruption prediction on JET

    International Nuclear Information System (INIS)

    Rattá, G.A.; Vega, J.; Murari, A.

    2012-01-01

    Highlights: ► A new signal selection methodology to improve disruption prediction is reported. ► The approach is based on Genetic Algorithms. ► An advanced predictor has been created with the new set of signals. ► The new system obtains considerably higher prediction rates. - Abstract: The early prediction of disruptions is an important aspect of the research in the field of Tokamak control. A very recent predictor, called “Advanced Predictor Of Disruptions” (APODIS), developed for the “Joint European Torus” (JET), implements the real time recognition of incoming disruptions with the best success rate achieved ever and an outstanding stability for long periods following training. In this article, a new methodology to select the set of the signals’ parameters in order to maximize the performance of the predictor is reported. The approach is based on “Genetic Algorithms” (GAs). With the feature selection derived from GAs, a new version of APODIS has been developed. The results are significantly better than the previous version not only in terms of success rates but also in extending the interval before the disruption in which reliable predictions are achieved. Correct disruption predictions with a success rate in excess of 90% have been achieved 200 ms before the time of the disruption. The predictor response is compared with that of JET's Protection System (JPS) and the ADODIS predictor is shown to be far superior. Both systems have been carefully tested with a wide number of discharges to understand their relative merits and the most profitable directions of further improvements.

  2. Application of Genetic Algorithm to Predict Optimal Sowing Region and Timing for Kentucky Bluegrass in China.

    Directory of Open Access Journals (Sweden)

    Erxu Pi

    Full Text Available Temperature is a predominant environmental factor affecting grass germination and distribution. Various thermal-germination models for prediction of grass seed germination have been reported, in which the relationship between temperature and germination were defined with kernel functions, such as quadratic or quintic function. However, their prediction accuracies warrant further improvements. The purpose of this study is to evaluate the relative prediction accuracies of genetic algorithm (GA models, which are automatically parameterized with observed germination data. The seeds of five P. pratensis (Kentucky bluegrass, KB cultivars were germinated under 36 day/night temperature regimes ranging from 5/5 to 40/40 °C with 5 °C increments. Results showed that optimal germination percentages of all five tested KB cultivars were observed under a fluctuating temperature regime of 20/25 °C. Meanwhile, the constant temperature regimes (e.g., 5/5, 10/10, 15/15 °C, etc. suppressed the germination of all five cultivars. Furthermore, the back propagation artificial neural network (BP-ANN algorithm was integrated to optimize temperature-germination response models from these observed germination data. It was found that integrations of GA-BP-ANN (back propagation aided genetic algorithm artificial neural network significantly reduced the Root Mean Square Error (RMSE values from 0.21~0.23 to 0.02~0.09. In an effort to provide a more reliable prediction of optimum sowing time for the tested KB cultivars in various regions in the country, the optimized GA-BP-ANN models were applied to map spatial and temporal germination percentages of blue grass cultivars in China. Our results demonstrate that the GA-BP-ANN model is a convenient and reliable option for constructing thermal-germination response models since it automates model parameterization and has excellent prediction accuracy.

  3. Improved feature selection based on genetic algorithms for real time disruption prediction on JET

    Energy Technology Data Exchange (ETDEWEB)

    Ratta, G.A., E-mail: garatta@gateme.unsj.edu.ar [GATEME, Facultad de Ingenieria, Universidad Nacional de San Juan, Avda. San Martin 1109 (O), 5400 San Juan (Argentina); JET EFDA, Culham Science Centre, OX14 3DB Abingdon (United Kingdom); Vega, J. [Asociacion EURATOM/CIEMAT para Fusion, Avda. Complutense, 40, 28040 Madrid (Spain); JET EFDA, Culham Science Centre, OX14 3DB Abingdon (United Kingdom); Murari, A. [Associazione EURATOM-ENEA per la Fusione, Consorzio RFX, 4-35127 Padova (Italy); JET EFDA, Culham Science Centre, OX14 3DB Abingdon (United Kingdom)

    2012-09-15

    Highlights: Black-Right-Pointing-Pointer A new signal selection methodology to improve disruption prediction is reported. Black-Right-Pointing-Pointer The approach is based on Genetic Algorithms. Black-Right-Pointing-Pointer An advanced predictor has been created with the new set of signals. Black-Right-Pointing-Pointer The new system obtains considerably higher prediction rates. - Abstract: The early prediction of disruptions is an important aspect of the research in the field of Tokamak control. A very recent predictor, called 'Advanced Predictor Of Disruptions' (APODIS), developed for the 'Joint European Torus' (JET), implements the real time recognition of incoming disruptions with the best success rate achieved ever and an outstanding stability for long periods following training. In this article, a new methodology to select the set of the signals' parameters in order to maximize the performance of the predictor is reported. The approach is based on 'Genetic Algorithms' (GAs). With the feature selection derived from GAs, a new version of APODIS has been developed. The results are significantly better than the previous version not only in terms of success rates but also in extending the interval before the disruption in which reliable predictions are achieved. Correct disruption predictions with a success rate in excess of 90% have been achieved 200 ms before the time of the disruption. The predictor response is compared with that of JET's Protection System (JPS) and the ADODIS predictor is shown to be far superior. Both systems have been carefully tested with a wide number of discharges to understand their relative merits and the most profitable directions of further improvements.

  4. Inclusion of biotic stress (consumer pressure) alters predictions from the stress gradient hypothesis

    NARCIS (Netherlands)

    Smit, Christian; Rietkerk, Max; Wassen, Martin J.

    2009-01-01

    The stress gradient hypothesis (SGH) predicts a shift from net negative interactions in benign environments towards net positive in harsh environments in ecological communities. While several studies found support for the SGH, others found evidence against it, leading to a debate on how nature and

  5. Can current moisture responses predict soil CO2 efflux under altered precipitation regimes? A synthesis of manipulation experiments

    DEFF Research Database (Denmark)

    Vicca, S.; Bahn, M.; Estiarte, M.

    2014-01-01

    to fluctuations in soil temperature and soil water content can be used to predict SCE under altered rainfall patterns. Of the 58 experiments for which we gathered SCE data, 20 were discarded because either too few data were available or inconsistencies precluded their incorporation in the analyses. The 38...... remaining experiments were used to test the hypothesis that a model parameterized with data from the control plots (using soil temperature and water content as predictor variables) could adequately predict SCE measured in the manipulated treatment. Only for 7 of these 38 experiments was this hypothesis...... strongly on establishing response functions across a broader range of precipitation regimes and soil moisture conditions. Such experiments should make accurate measurements of water availability, should conduct high-frequency SCE measurements, and should consider both instantaneous responses...

  6. Testing the Prediction of Iron Alteration Minerals on Low Albedo Asteroids

    Science.gov (United States)

    Jarvis, K. S.; Vilas, Faith; Howell, E.; Kelley, M.; Cochran, A.

    1999-01-01

    Absorption features centered near 0.60 - 0.65 and 0.80 - 0.90 micron were identified in the spectra of three low-albedo main-belt (165, 368, 877) and two low-albedo outer-belt (225, 334) asteroids (Vilas et al., Icarus, v. 109,274,1994). The absorption features were attributed to charge transfer transitions in iron alteration minerals such as goethite, hematite, and jarosite, all products of aqueous alteration. Concurrently, Jarvis et al. (LPSC XXIV, 715, 1993) presented additional spectra of low-albedo asteroids that had absorption features centered near 0.60 - 0.65 micron without the longer wavelength feature. Since these two features in iron oxides originate from the same ground state, and the longer wavelength feature requires less energy to exist, the single shorter wavelength feature cannot be caused by the iron alteration minerals. In addition, spectra of minerals such as hematite and goethite show a rapid increase in reflectance beginning near 0.5 micron absent in the low-albedo asteroid spectra. The absence of this rise has been attributed to its suppresion from opaques in the surface material. Spectra on more than one night were available for only one of these five asteroids, 225 Henrietta, and showed good repeatability of the 0.65-micron feature. We have acquired additional spectra of all five asteroids in order to test the repeatability of the 0.65-micron feature, and the presence and repeatability of the features centered near 0.8 - 0.9 micron. We specifically will test the possibility that longer wavelength features could be caused by incomplete removal of telluric water. Asteroid 877 Walkure is a member of the Nysa-Hertha family, and will be compared to spectra of other members of that family. Data were acquired in 1996 and 1999 on the 2.1-m telescope with a facility cassegrain spectrograph, McDonald Observatory, Univ. Of Texas, and the 1.5-m telescope with facility cassegrain spectrograph at CTIO. This research is supported by the NASA Planetary

  7. DNA Mismatch Repair Deficiency in Rectal Cancer: Benchmarking Its Impact on Prognosis, Neoadjuvant Response Prediction, and Clinical Cancer Genetics.

    Science.gov (United States)

    de Rosa, Nicole; Rodriguez-Bigas, Miguel A; Chang, George J; Veerapong, Jula; Borras, Ester; Krishnan, Sunil; Bednarski, Brian; Messick, Craig A; Skibber, John M; Feig, Barry W; Lynch, Patrick M; Vilar, Eduardo; You, Y Nancy

    2016-09-01

    DNA mismatch repair deficiency (dMMR) hallmarks consensus molecular subtype 1 of colorectal cancer. It is being routinely tested, but little is known about dMMR rectal cancers. The efficacy of novel treatment strategies cannot be established without benchmarking the outcomes of dMMR rectal cancer with current therapy. We aimed to delineate the impact of dMMR on prognosis, the predicted response to fluoropyrimidine-based neoadjuvant therapy, and implications of germline alterations in the MMR genes in rectal cancer. Between 1992 and 2012, 62 patients with dMMR rectal cancers underwent multimodality therapy. Oncologic treatment and outcomes as well as clinical genetics work-up were examined. Overall and rectal cancer-specific survival were calculated by the Kaplan-Meier method. The median age at diagnosis was 41 years. MMR deficiency was most commonly due to alterations in MSH2 (53%) or MSH6 (23%). After a median follow-up of 6.8 years, the 5-year rectal cancer-specific survival was 100% for stage I and II, 85.1% for stage III, and 60.0% for stage IV disease. Fluoropyrimidine-based neoadjuvant chemoradiation was associated with a complete pathologic response rate of 27.6%. The extent of surgical resection was influenced by synchronous colonic disease at presentation, tumor height, clinical stage, and pelvic radiation. An informed decision for a limited resection focusing on proctectomy did not compromise overall survival. Five of the 11 (45.5%) deaths during follow-up were due to extracolorectal malignancies. dMMR rectal cancer had excellent prognosis and pathologic response with current multimodality therapy including an individualized surgical treatment plan. Identification of a dMMR rectal cancer should trigger germline testing, followed by lifelong surveillance for both colorectal and extracolorectal malignancies. We herein provide genotype-specific outcome benchmarks for comparison with novel interventions. © 2016 by American Society of Clinical Oncology.

  8. Genetic Learning of Fuzzy Parameters in Predictive and Decision Support Modelling

    Directory of Open Access Journals (Sweden)

    Nebot

    2012-04-01

    Full Text Available In this research a genetic fuzzy system (GFS is proposed that performs discretization parameter learning in the context of the Fuzzy Inductive Reasoning (FIR methodology and the Linguistic Rule FIR (LR-FIR algorithm. The main goal of the GFS is to take advantage of the potentialities of GAs to learn the fuzzification parameters of the FIR and LR-FIR approaches in order to obtain reliable and useful predictive (FIR models and decision support (LR-FIR models. The GFS is evaluated in an e-learning context.

  9. Genetic risk prediction using a spatial autoregressive model with adaptive lasso.

    Science.gov (United States)

    Wen, Yalu; Shen, Xiaoxi; Lu, Qing

    2018-05-31

    With rapidly evolving high-throughput technologies, studies are being initiated to accelerate the process toward precision medicine. The collection of the vast amounts of sequencing data provides us with great opportunities to systematically study the role of a deep catalog of sequencing variants in risk prediction. Nevertheless, the massive amount of noise signals and low frequencies of rare variants in sequencing data pose great analytical challenges on risk prediction modeling. Motivated by the development in spatial statistics, we propose a spatial autoregressive model with adaptive lasso (SARAL) for risk prediction modeling using high-dimensional sequencing data. The SARAL is a set-based approach, and thus, it reduces the data dimension and accumulates genetic effects within a single-nucleotide variant (SNV) set. Moreover, it allows different SNV sets having various magnitudes and directions of effect sizes, which reflects the nature of complex diseases. With the adaptive lasso implemented, SARAL can shrink the effects of noise SNV sets to be zero and, thus, further improve prediction accuracy. Through simulation studies, we demonstrate that, overall, SARAL is comparable to, if not better than, the genomic best linear unbiased prediction method. The method is further illustrated by an application to the sequencing data from the Alzheimer's Disease Neuroimaging Initiative. Copyright © 2018 John Wiley & Sons, Ltd.

  10. Linear genetic programming application for successive-station monthly streamflow prediction

    Science.gov (United States)

    Danandeh Mehr, Ali; Kahya, Ercan; Yerdelen, Cahit

    2014-09-01

    In recent decades, artificial intelligence (AI) techniques have been pronounced as a branch of computer science to model wide range of hydrological phenomena. A number of researches have been still comparing these techniques in order to find more effective approaches in terms of accuracy and applicability. In this study, we examined the ability of linear genetic programming (LGP) technique to model successive-station monthly streamflow process, as an applied alternative for streamflow prediction. A comparative efficiency study between LGP and three different artificial neural network algorithms, namely feed forward back propagation (FFBP), generalized regression neural networks (GRNN), and radial basis function (RBF), has also been presented in this study. For this aim, firstly, we put forward six different successive-station monthly streamflow prediction scenarios subjected to training by LGP and FFBP using the field data recorded at two gauging stations on Çoruh River, Turkey. Based on Nash-Sutcliffe and root mean squared error measures, we then compared the efficiency of these techniques and selected the best prediction scenario. Eventually, GRNN and RBF algorithms were utilized to restructure the selected scenario and to compare with corresponding FFBP and LGP. Our results indicated the promising role of LGP for successive-station monthly streamflow prediction providing more accurate results than those of all the ANN algorithms. We found an explicit LGP-based expression evolved by only the basic arithmetic functions as the best prediction model for the river, which uses the records of the both target and upstream stations.

  11. A combination of compositional index and genetic algorithm for predicting transmembrane helical segments.

    Directory of Open Access Journals (Sweden)

    Nazar Zaki

    Full Text Available Transmembrane helix (TMH topology prediction is becoming a focal problem in bioinformatics because the structure of TM proteins is difficult to determine using experimental methods. Therefore, methods that can computationally predict the topology of helical membrane proteins are highly desirable. In this paper we introduce TMHindex, a method for detecting TMH segments using only the amino acid sequence information. Each amino acid in a protein sequence is represented by a Compositional Index, which is deduced from a combination of the difference in amino acid occurrences in TMH and non-TMH segments in training protein sequences and the amino acid composition information. Furthermore, a genetic algorithm was employed to find the optimal threshold value for the separation of TMH segments from non-TMH segments. The method successfully predicted 376 out of the 378 TMH segments in a dataset consisting of 70 test protein sequences. The sensitivity and specificity for classifying each amino acid in every protein sequence in the dataset was 0.901 and 0.865, respectively. To assess the generality of TMHindex, we also tested the approach on another standard 73-protein 3D helix dataset. TMHindex correctly predicted 91.8% of proteins based on TM segments. The level of the accuracy achieved using TMHindex in comparison to other recent approaches for predicting the topology of TM proteins is a strong argument in favor of our proposed method.The datasets, software together with supplementary materials are available at: http://faculty.uaeu.ac.ae/nzaki/TMHindex.htm.

  12. Detecting Human Hydrologic Alteration from Diversion Hydropower Requires Universal Flow Prediction Tools: A Proposed Framework for Flow Prediction in Poorly-gauged, Regulated Rivers

    Science.gov (United States)

    Kibler, K. M.; Alipour, M.

    2016-12-01

    Achieving the universal energy access Sustainable Development Goal will require great investment in renewable energy infrastructure in the developing world. Much growth in the renewable sector will come from new hydropower projects, including small and diversion hydropower in remote and mountainous regions. Yet, human impacts to hydrological systems from diversion hydropower are poorly described. Diversion hydropower is often implemented in ungauged rivers, thus detection of impact requires flow analysis tools suited to prediction in poorly-gauged and human-altered catchments. We conduct a comprehensive analysis of hydrologic alteration in 32 rivers developed with diversion hydropower in southwestern China. As flow data are sparse, we devise an approach for estimating streamflow during pre- and post-development periods, drawing upon a decade of research into prediction in ungauged basins. We apply a rainfall-runoff model, parameterized and forced exclusively with global-scale data, in hydrologically-similar gauged and ungauged catchments. Uncertain "soft" data are incorporated through fuzzy numbers and confidence-based weighting, and a multi-criteria objective function is applied to evaluate model performance. Testing indicates that the proposed framework returns superior performance (NSE = 0.77) as compared to models parameterized by rote calibration (NSE = 0.62). Confident that the models are providing `the right answer for the right reasons', our analysis of hydrologic alteration based on simulated flows indicates statistically significant hydrologic effects of diversion hydropower across many rivers. Mean annual flows, 7-day minimum and 7-day maximum flows decreased. Frequency and duration of flow exceeding Q25 decreased while duration of flows sustained below the Q75 increased substantially. Hydrograph rise and fall rates and flow constancy increased. The proposed methodology may be applied to improve diversion hydropower design in data-limited regions.

  13. Targeted capture massively parallel sequencing analysis of LCIS and invasive lobular cancer: Repertoire of somatic genetic alterations and clonal relationships.

    Science.gov (United States)

    Sakr, Rita A; Schizas, Michail; Carniello, Jose V Scarpa; Ng, Charlotte K Y; Piscuoglio, Salvatore; Giri, Dilip; Andrade, Victor P; De Brot, Marina; Lim, Raymond S; Towers, Russell; Weigelt, Britta; Reis-Filho, Jorge S; King, Tari A

    2016-02-01

    Lobular carcinoma in situ (LCIS) has been proposed as a non-obligate precursor of invasive lobular carcinoma (ILC). Here we sought to define the repertoire of somatic genetic alterations in pure LCIS and in synchronous LCIS and ILC using targeted massively parallel sequencing. DNA samples extracted from microdissected LCIS, ILC and matched normal breast tissue or peripheral blood from 30 patients were subjected to massively parallel sequencing targeting all exons of 273 genes, including the genes most frequently mutated in breast cancer and DNA repair-related genes. Single nucleotide variants and insertions and deletions were identified using state-of-the-art bioinformatics approaches. The constellation of somatic mutations found in LCIS (n = 34) and ILC (n = 21) were similar, with the most frequently mutated genes being CDH1 (56% and 66%, respectively), PIK3CA (41% and 52%, respectively) and CBFB (12% and 19%, respectively). Among 19 LCIS and ILC synchronous pairs, 14 (74%) had at least one identical mutation in common, including identical PIK3CA and CDH1 mutations. Paired analysis of independent foci of LCIS from 3 breasts revealed at least one common mutation in each of the 3 pairs (CDH1, PIK3CA, CBFB and PKHD1L1). LCIS and ILC have a similar repertoire of somatic mutations, with PIK3CA and CDH1 being the most frequently mutated genes. The presence of identical mutations between LCIS-LCIS and LCIS-ILC pairs demonstrates that LCIS is a clonal neoplastic lesion, and provides additional evidence that at least some LCIS are non-obligate precursors of ILC. Copyright © 2015 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

  14. An altered redox balance and increased genetic instability characterize primary fibroblasts derived from xeroderma pigmentosum group A patients.

    Science.gov (United States)

    Parlanti, Eleonora; Pietraforte, Donatella; Iorio, Egidio; Visentin, Sergio; De Nuccio, Chiara; Zijno, Andrea; D'Errico, Mariarosaria; Simonelli, Valeria; Sanchez, Massimo; Fattibene, Paola; Falchi, Mario; Dogliotti, Eugenia

    2015-12-01

    Xeroderma pigmentosum (XP)-A patients are characterized by increased solar skin carcinogenesis and present also neurodegeneration. XPA deficiency is associated with defective nucleotide excision repair (NER) and increased basal levels of oxidatively induced DNA damage. In this study we search for the origin of increased levels of oxidatively generated DNA lesions in XP-A cell genome and then address the question of whether increased oxidative stress might drive genetic instability. We show that XP-A human primary fibroblasts present increased levels and different types of intracellular reactive oxygen species (ROS) as compared to normal fibroblasts, with O₂₋• and H₂O₂ being the major reactive species. Moreover, XP-A cells are characterized by decreased reduced glutathione (GSH)/oxidized glutathione (GSSG) ratios as compared to normal fibroblasts. The significant increase of ROS levels and the alteration of the glutathione redox state following silencing of XPA confirmed the causal relationship between a functional XPA and the control of redox balance. Proton nuclear magnetic resonance (¹H NMR) analysis of the metabolic profile revealed a more glycolytic metabolism and higher ATP levels in XP-A than in normal primary fibroblasts. This perturbation of bioenergetics is associated with different morphology and response of mitochondria to targeted toxicants. In line with cancer susceptibility, XP-A primary fibroblasts showed increased spontaneous micronuclei (MN) frequency, a hallmark of cancer risk. The increased MN frequency was not affected by inhibition of ROS to normal levels by N-acetyl-L-cysteine. Copyright © 2015 Elsevier B.V. All rights reserved.

  15. Application of genetic algorithm - multiple linear regressions to predict the activity of RSK inhibitors

    Directory of Open Access Journals (Sweden)

    Avval Zhila Mohajeri

    2015-01-01

    Full Text Available This paper deals with developing a linear quantitative structure-activity relationship (QSAR model for predicting the RSK inhibition activity of some new compounds. A dataset consisting of 62 pyrazino [1,2-α] indole, diazepino [1,2-α] indole, and imidazole derivatives with known inhibitory activities was used. Multiple linear regressions (MLR technique combined with the stepwise (SW and the genetic algorithm (GA methods as variable selection tools was employed. For more checking stability, robustness and predictability of the proposed models, internal and external validation techniques were used. Comparison of the results obtained, indicate that the GA-MLR model is superior to the SW-MLR model and that it isapplicable for designing novel RSK inhibitors.

  16. Multi-gene genetic programming based predictive models for municipal solid waste gasification in a fluidized bed gasifier.

    Science.gov (United States)

    Pandey, Daya Shankar; Pan, Indranil; Das, Saptarshi; Leahy, James J; Kwapinski, Witold

    2015-03-01

    A multi-gene genetic programming technique is proposed as a new method to predict syngas yield production and the lower heating value for municipal solid waste gasification in a fluidized bed gasifier. The study shows that the predicted outputs of the municipal solid waste gasification process are in good agreement with the experimental dataset and also generalise well to validation (untrained) data. Published experimental datasets are used for model training and validation purposes. The results show the effectiveness of the genetic programming technique for solving complex nonlinear regression problems. The multi-gene genetic programming are also compared with a single-gene genetic programming model to show the relative merits and demerits of the technique. This study demonstrates that the genetic programming based data-driven modelling strategy can be a good candidate for developing models for other types of fuels as well. Copyright © 2014 Elsevier Ltd. All rights reserved.

  17. STOPGAP: a database for systematic target opportunity assessment by genetic association predictions.

    Science.gov (United States)

    Shen, Judong; Song, Kijoung; Slater, Andrew J; Ferrero, Enrico; Nelson, Matthew R

    2017-09-01

    We developed the STOPGAP (Systematic Target OPportunity assessment by Genetic Association Predictions) database, an extensive catalog of human genetic associations mapped to effector gene candidates. STOPGAP draws on a variety of publicly available GWAS associations, linkage disequilibrium (LD) measures, functional genomic and variant annotation sources. Algorithms were developed to merge the association data, partition associations into non-overlapping LD clusters, map variants to genes and produce a variant-to-gene score used to rank the relative confidence among potential effector genes. This database can be used for a multitude of investigations into the genes and genetic mechanisms underlying inter-individual variation in human traits, as well as supporting drug discovery applications. Shell, R, Perl and Python scripts and STOPGAP R data files (version 2.5.1 at publication) are available at https://github.com/StatGenPRD/STOPGAP . Some of the most useful STOPGAP fields can be queried through an R Shiny web application at http://stopgapwebapp.com . matthew.r.nelson@gsk.com. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  18. A Neuro-genetic Based Short-term Forecasting Framework for Network Intrusion Prediction System

    Institute of Scientific and Technical Information of China (English)

    Siva S. Sivatha Sindhu; S. Geetha; M. Marikannan; A. Kannan

    2009-01-01

    Information systems are one of the most rapidly changing and vulnerable systems, where security is a major issue. The number of security-breaking attempts originating inside organizations is increasing steadily. Attacks made in this way, usually done by "authorized" users of the system, cannot be immediately traced. Because the idea of filtering the traffic at the entrance door, by using firewalls and the like, is not completely successful, the use of intrusion detection systems should be considered to increase the defense capacity of an information system. An intrusion detection system (IDS) is usually working in a dynamically changing environment, which forces continuous tuning of the intrusion detection model, in order to maintain sufficient performance. The manual tuning process required by current IDS depends on the system operators in working out the tuning solution and in integrating it into the detection model. Furthermore, an extensive effort is required to tackle the newly evolving attacks and a deep study is necessary to categorize it into the respective classes. To reduce this dependence, an automatically evolving anomaly IDS using neuro-genetic algorithm is presented. The proposed system automatically tunes the detection model on the fly according to the feedback provided by the system operator when false predictions are encountered. The system has been evaluated using the Knowledge Discovery in Databases Conference (KDD 2009) intrusion detection dataset. Genetic paradigm is employed to choose the predominant features, which reveal the occurrence of intrusions. The neuro-genetic IDS (NGIDS) involves calculation of weightage value for each of the categorical attributes so that data of uniform representation can be processed by the neuro-genetic algorithm. In this system unauthorized invasion of a user are identified and newer types of attacks are sensed and classified respectively by the neuro-genetic algorithm. The experimental results obtained in this

  19. Historical precipitation predictably alters the shape and magnitude of microbial functional response to soil moisture.

    Science.gov (United States)

    Averill, Colin; Waring, Bonnie G; Hawkes, Christine V

    2016-05-01

    Soil moisture constrains the activity of decomposer soil microorganisms, and in turn the rate at which soil carbon returns to the atmosphere. While increases in soil moisture are generally associated with increased microbial activity, historical climate may constrain current microbial responses to moisture. However, it is not known if variation in the shape and magnitude of microbial functional responses to soil moisture can be predicted from historical climate at regional scales. To address this problem, we measured soil enzyme activity at 12 sites across a broad climate gradient spanning 442-887 mm mean annual precipitation. Measurements were made eight times over 21 months to maximize sampling during different moisture conditions. We then fit saturating functions of enzyme activity to soil moisture and extracted half saturation and maximum activity parameter values from model fits. We found that 50% of the variation in maximum activity parameters across sites could be predicted by 30-year mean annual precipitation, an indicator of historical climate, and that the effect is independent of variation in temperature, soil texture, or soil carbon concentration. Based on this finding, we suggest that variation in the shape and magnitude of soil microbial response to soil moisture due to historical climate may be remarkably predictable at regional scales, and this approach may extend to other systems. If historical contingencies on microbial activities prove to be persistent in the face of environmental change, this approach also provides a framework for incorporating historical climate effects into biogeochemical models simulating future global change scenarios. © 2016 John Wiley & Sons Ltd.

  20. Predicting future changes in Muskegon River Watershed game fish distributions under future land cover alteration and climate change scenarios

    Science.gov (United States)

    Steen, Paul J.; Wiley, Michael J.; Schaeffer, Jeffrey S.

    2010-01-01

    Future alterations in land cover and climate are likely to cause substantial changes in the ranges of fish species. Predictive distribution models are an important tool for assessing the probability that these changes will cause increases or decreases in or the extirpation of species. Classification tree models that predict the probability of game fish presence were applied to the streams of the Muskegon River watershed, Michigan. The models were used to study three potential future scenarios: (1) land cover change only, (2) land cover change and a 3°C increase in air temperature by 2100, and (3) land cover change and a 5°C increase in air temperature by 2100. The analysis indicated that the expected change in air temperature and subsequent change in water temperatures would result in the decline of coldwater fish in the Muskegon watershed by the end of the 21st century while cool- and warmwater species would significantly increase their ranges. The greatest decline detected was a 90% reduction in the probability that brook trout Salvelinus fontinalis would occur in Bigelow Creek. The greatest increase was a 276% increase in the probability that northern pike Esox lucius would occur in the Middle Branch River. Changes in land cover are expected to cause large changes in a few fish species, such as walleye Sander vitreus and Chinook salmon Oncorhynchus tshawytscha, but not to drive major changes in species composition. Managers can alter stream environmental conditions to maximize the probability that species will reside in particular stream reaches through application of the classification tree models. Such models represent a good way to predict future changes, as they give quantitative estimates of the n-dimensional niches for particular species.

  1. A Genetic Algorithm Based Support Vector Machine Model for Blood-Brain Barrier Penetration Prediction

    Directory of Open Access Journals (Sweden)

    Daqing Zhang

    2015-01-01

    Full Text Available Blood-brain barrier (BBB is a highly complex physical barrier determining what substances are allowed to enter the brain. Support vector machine (SVM is a kernel-based machine learning method that is widely used in QSAR study. For a successful SVM model, the kernel parameters for SVM and feature subset selection are the most important factors affecting prediction accuracy. In most studies, they are treated as two independent problems, but it has been proven that they could affect each other. We designed and implemented genetic algorithm (GA to optimize kernel parameters and feature subset selection for SVM regression and applied it to the BBB penetration prediction. The results show that our GA/SVM model is more accurate than other currently available log BB models. Therefore, to optimize both SVM parameters and feature subset simultaneously with genetic algorithm is a better approach than other methods that treat the two problems separately. Analysis of our log BB model suggests that carboxylic acid group, polar surface area (PSA/hydrogen-bonding ability, lipophilicity, and molecular charge play important role in BBB penetration. Among those properties relevant to BBB penetration, lipophilicity could enhance the BBB penetration while all the others are negatively correlated with BBB penetration.

  2. The impact of predictive genetic testing for hereditary nonpolyposis colorectal cancer: three years after testing.

    Science.gov (United States)

    Collins, Veronica R; Meiser, Bettina; Ukoumunne, Obioha C; Gaff, Clara; St John, D James; Halliday, Jane L

    2007-05-01

    To fully assess predictive genetic testing programs, it is important to assess outcomes over periods of time longer than the 1-year follow-up reported in the literature. We conducted a 3-year study of individuals who received predictive genetic test results for previously identified familial mutations in Australian Familial Cancer Clinics. Questionnaires were sent before attendance at the familial cancer clinic and 2 weeks, 4 months, 1 year, and 3 years after receiving test results. Psychological measures were included each time, and preventive behaviors were assessed at baseline and 1 and 3 years. Psychological measures were adjusted for age, gender, and baseline score. The study included 19 carriers and 54 non-carriers. We previously reported an increase in mean cancer-specific distress in carriers at 2 weeks with a return to baseline levels by 12 months. This level was maintained until 3 years. Non-carriers showed sustained decreases after testing with a significantly lower level at 3 years compared with baseline (P depression and anxiety scores did not differ between carriers and non-carriers and, at 3 years, were similar to baseline. All carriers and 7% of non-carriers had had a colonoscopy by 3 years, and 69% of 13 female carriers had undergone gynecological screening in the previous 2 years. Prophylactic surgery was rare. This report of long-term data indicates appropriate screening and improved psychological measures for non-carriers with no evidence of undue psychological distress in carriers of hereditary nonpolyposis colorectal cancer mutations.

  3. What should we want to know about our future? A Kantian view on predictive genetic testing.

    Science.gov (United States)

    Heinrichs, Bert

    2005-01-01

    Recent advances in genomic research have led to the development of new diagnostic tools, including tests which make it possible to predict the future occurrence of monogenetic diseases (e.g. Chorea Huntington) or to determine increased susceptibilities to the future development of more complex diseases (e.g. breast cancer). The use of such tests raises a number of ethical, legal and social issues which are usually discussed in terms of rights. However, in the context of predictive genetic tests a key question arises which lies beyond the concept of rights, namely, What should we want to know about our future? In the following I shall discuss this question against the background of Kant's Doctrine of Virtue. It will be demonstrated that the system of duties of virtue that Kant elaborates in the second part of his Metaphysics of Morals offers a theoretical framework for addressing the question of a proper scope of future knowledge as provided by genetic tests. This approach can serve as a source of moral guidance complementary to a justice perspective. It does, however, not rest on the-rather problematic--claim to be able to define what the "good life" is.

  4. Externalizing Problems in Childhood and Adolescence Predict Subsequent Educational Achievement but for Different Genetic and Environmental Reasons

    Science.gov (United States)

    Lewis, Gary J.; Asbury, Kathryn; Plomin, Robert

    2017-01-01

    Background: Childhood behavior problems predict subsequent educational achievement; however, little research has examined the etiology of these links using a longitudinal twin design. Moreover, it is unknown whether genetic and environmental innovations provide incremental prediction for educational achievement from childhood to adolescence.…

  5. Predictive genetic testing in children and adults: a study of emotional impact.

    Science.gov (United States)

    Michie, S; Bobrow, M; Marteau, T M

    2001-08-01

    To determine whether, following predictive genetic testing for familial adenomatous polyposis (FAP), children or adults receiving positive results experience clinically significant levels of anxiety or depression, and whether children receiving positive results experience higher levels of anxiety or depression than adults receiving positive results. Two studies, one cross sectional and one prospective. 208 unaffected subjects (148 adults and 60 children) at risk for FAP who have undergone genetic testing since 1990. anxiety, depression; independent variables: test results, demographic measures, psychological resources (optimism, self-esteem). Study 1. In children receiving positive results, mean scores for anxiety and depression were within the normal range. There was a trend for children receiving positive results to be more anxious and depressed than those receiving negative results. In adults, mean scores for anxiety were within the normal range for those receiving negative results, but were in the clinical range for those receiving positive results, with 43% (95% CI 23-65) of the latter having scores in this range. Regardless of test result, adults were more likely to be clinically anxious if they were low in optimism or self-esteem. Children receiving positive or negative results did not experience greater anxiety or depression than adults. Study 2. For children receiving a positive test result, mean scores for anxiety, depression, and self-esteem were unchanged over the year following the result, while mean anxiety scores decreased and self-esteem increased after receipt of a negative test result over the same period of time. Children, as a group, did not show clinically significant distress over the first year following predictive genetic testing. Adults were more likely to be clinically anxious if they received a positive result or were low in optimism or self-esteem, with interacting effects. The association between anxiety, self-esteem, and optimism

  6. Antigen recognition by cloned cytotoxic T lymphocytes follows rules predicted by the altered-self hypothesis

    International Nuclear Information System (INIS)

    Huenig, T.R.; Bevan, M.J.

    1982-01-01

    Radiation chimeras prepared by injecting H-2 heterozygous F1 stem cells into lethally irradiated parental hosts show a marked, but not absolute, preference for host-type H-2 antigens in the H-2-restricted cytotoxic T lymphocyte (CTL) response to minor histocompatibility (minor H) antigens. We have selected for the anti-minor HCTL that are restricted to the parental H-2 type absent from the chimeric host and found that in two out of eight cases, such CTL lysed target cells of either parental H-2 type. From one of these CTL populations that lysed H-2d and H-2k target cells expressing BALB minor H antigens, clones were derived and further analyzed. The results showed that: (a) lysis of both H-2d and H-2k target cells was H-2 restricted; (b) H-2d restriction mapped to Dd, and H-2k restriction mapped to Kk; (c) testing against various H-2d and H-2k strains of different and partially overlapping minor H backgrounds as well as against the appropriate F1 crosses revealed that in Dd- and Kk-restricted killing, different minor H antigens were recognized. In a second system, a CTL population was selected from normal (H-2d x H-2k)F1 mice that was specific for H-2d plus minor H antigens and for H-2k plus trinitrophenylated bovine serum albumin. We interpret these findings in terms of the altered-self hypothesis: The association of one H-2 antigen with one conventional antigen X may be recognized by the same T cell receptor specific for the complex formed by a different H-2 antigen in association with a second conventional antigen Y. The implications of these observations for the influence of self H-2 on the generation of the T cell receptor repertoire are discussed

  7. The predictability of frequency-altered auditory feedback changes the weighting of feedback and feedforward input for speech motor control.

    Science.gov (United States)

    Scheerer, Nichole E; Jones, Jeffery A

    2014-12-01

    Speech production requires the combined effort of a feedback control system driven by sensory feedback, and a feedforward control system driven by internal models. However, the factors that dictate the relative weighting of these feedback and feedforward control systems are unclear. In this event-related potential (ERP) study, participants produced vocalisations while being exposed to blocks of frequency-altered feedback (FAF) perturbations that were either predictable in magnitude (consistently either 50 or 100 cents) or unpredictable in magnitude (50- and 100-cent perturbations varying randomly within each vocalisation). Vocal and P1-N1-P2 ERP responses revealed decreases in the magnitude and trial-to-trial variability of vocal responses, smaller N1 amplitudes, and shorter vocal, P1 and N1 response latencies following predictable FAF perturbation magnitudes. In addition, vocal response magnitudes correlated with N1 amplitudes, vocal response latencies, and P2 latencies. This pattern of results suggests that after repeated exposure to predictable FAF perturbations, the contribution of the feedforward control system increases. Examination of the presentation order of the FAF perturbations revealed smaller compensatory responses, smaller P1 and P2 amplitudes, and shorter N1 latencies when the block of predictable 100-cent perturbations occurred prior to the block of predictable 50-cent perturbations. These results suggest that exposure to large perturbations modulates responses to subsequent perturbations of equal or smaller size. Similarly, exposure to a 100-cent perturbation prior to a 50-cent perturbation within a vocalisation decreased the magnitude of vocal and N1 responses, but increased P1 and P2 latencies. Thus, exposure to a single perturbation can affect responses to subsequent perturbations. © 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  8. Modeling and predictions of biphasic mechanosensitive cell migration altered by cell-intrinsic properties and matrix confinement.

    Science.gov (United States)

    Pathak, Amit

    2018-04-12

    Motile cells sense the stiffness of their extracellular matrix (ECM) through adhesions and respond by modulating the generated forces, which in turn lead to varying mechanosensitive migration phenotypes. Through modeling and experiments, cell migration speed is known to vary with matrix stiffness in a biphasic manner, with optimal motility at an intermediate stiffness. Here, we present a two-dimensional cell model defined by nodes and elements, integrated with subcellular modeling components corresponding to mechanotransductive adhesion formation, force generation, protrusions and node displacement. On 2D matrices, our calculations reproduce the classic biphasic dependence of migration speed on matrix stiffness and predict that cell types with higher force-generating ability do not slow down on very stiff matrices, thus disabling the biphasic response. We also predict that cell types defined by lower number of total receptors require stiffer matrices for optimal motility, which also limits the biphasic response. For a cell type with robust biphasic migration on 2D surface, simulations in channel-like confined environments of varying width and height predict faster migration in more confined matrices. Simulations performed in shallower channels predict that the biphasic mechanosensitive cell migration response is more robust on 2D micro-patterns as compared to the channel-like 3D confinement. Thus, variations in the dimensionality of matrix confinement alters the way migratory cells sense and respond to the matrix stiffness. Our calculations reveal new phenotypes of stiffness- and topography-sensitive cell migration that critically depend on both cell-intrinsic and matrix properties. These predictions may inform our understanding of various mechanosensitive modes of cell motility that could enable tumor invasion through topographically heterogeneous microenvironments. © 2018 IOP Publishing Ltd.

  9. A Pareto-optimal moving average multigene genetic programming model for daily streamflow prediction

    Science.gov (United States)

    Danandeh Mehr, Ali; Kahya, Ercan

    2017-06-01

    Genetic programming (GP) is able to systematically explore alternative model structures of different accuracy and complexity from observed input and output data. The effectiveness of GP in hydrological system identification has been recognized in recent studies. However, selecting a parsimonious (accurate and simple) model from such alternatives still remains a question. This paper proposes a Pareto-optimal moving average multigene genetic programming (MA-MGGP) approach to develop a parsimonious model for single-station streamflow prediction. The three main components of the approach that take us from observed data to a validated model are: (1) data pre-processing, (2) system identification and (3) system simplification. The data pre-processing ingredient uses a simple moving average filter to diminish the lagged prediction effect of stand-alone data-driven models. The multigene ingredient of the model tends to identify the underlying nonlinear system with expressions simpler than classical monolithic GP and, eventually simplification component exploits Pareto front plot to select a parsimonious model through an interactive complexity-efficiency trade-off. The approach was tested using the daily streamflow records from a station on Senoz Stream, Turkey. Comparing to the efficiency results of stand-alone GP, MGGP, and conventional multi linear regression prediction models as benchmarks, the proposed Pareto-optimal MA-MGGP model put forward a parsimonious solution, which has a noteworthy importance of being applied in practice. In addition, the approach allows the user to enter human insight into the problem to examine evolved models and pick the best performing programs out for further analysis.

  10. Predicting how altering propagule pressure changes establishment rates of biological invaders across species pools.

    Science.gov (United States)

    Brockerhoff, Eckehard G; Kimberley, Mark; Liebhold, Andrew M; Haack, Robert A; Cavey, Joseph F

    2014-03-01

    Biological invasions resulting from international trade can cause major environmental and economic impacts. Propagule pressure is perhaps the most important factor influencing establishment, although actual arrival rates of species are rarely recorded. Furthermore, the pool of potential invaders includes many species that vary in their arrival rate and establishment potential. Therefore, we stress that it is essential to consider the size and composition of species pools arriving from source regions when estimating probabilities of establishment and effects of pathway infestation rates. To address this, we developed a novel framework and modeling approach to enable prediction of future establishments in relation to changes in arrival rate across entire species pools. We utilized 13 828 border interception records from the United States and New Zealand for 444 true bark beetle (Scolytinae) and longhorned beetle (Cerambycidae) species detected between 1949 and 2008 as proxies for arrival rates to model the relationship between arrival and establishment rates. Nonlinearity in this relationship implies that measures intended to reduce the unintended transport of potential invaders (such as phytosanitary treatments) must be highly effective in order to substantially reduce the rate of future invasions, particularly if trade volumes continue to increase.

  11. Disturbance Regimes Predictably Alter Diversity in an Ecologically Complex Bacterial System

    Directory of Open Access Journals (Sweden)

    Sean M. Gibbons

    2016-12-01

    Full Text Available Diversity is often associated with the functional stability of ecological communities from microbes to macroorganisms. Understanding how diversity responds to environmental perturbations and the consequences of this relationship for ecosystem function are thus central challenges in microbial ecology. Unimodal diversity-disturbance relationships, in which maximum diversity occurs at intermediate levels of disturbance, have been predicted for ecosystems where life history tradeoffs separate organisms along a disturbance gradient. However, empirical support for such peaked relationships in macrosystems is mixed, and few studies have explored these relationships in microbial systems. Here we use complex microbial microcosm communities to systematically determine diversity-disturbance relationships over a range of disturbance regimes. We observed a reproducible switch between community states, which gave rise to transient diversity maxima when community states were forced to mix. Communities showed reduced compositional stability when diversity was highest. To further explore these dynamics, we formulated a simple model that reveals specific regimes under which diversity maxima are stable. Together, our results show how both unimodal and non-unimodal diversity-disturbance relationships can be observed as a system switches between two distinct microbial community states; this process likely occurs across a wide range of spatially and temporally heterogeneous microbial ecosystems.

  12. Externalizing problems in childhood and adolescence predict subsequent educational achievement but for different genetic and environmental reasons.

    Science.gov (United States)

    Lewis, Gary J; Asbury, Kathryn; Plomin, Robert

    2017-03-01

    Childhood behavior problems predict subsequent educational achievement; however, little research has examined the etiology of these links using a longitudinal twin design. Moreover, it is unknown whether genetic and environmental innovations provide incremental prediction for educational achievement from childhood to adolescence. We examined genetic and environmental influences on parental ratings of behavior problems across childhood (age 4) and adolescence (ages 12 and 16) as predictors of educational achievement at age 16 using a longitudinal classical twin design. Shared-environmental influences on anxiety, conduct problems, and peer problems at age 4 predicted educational achievement at age 16. Genetic influences on the externalizing behaviors of conduct problems and hyperactivity at age 4 predicted educational achievement at age 16. Moreover, novel genetic and (to a lesser extent) nonshared-environmental influences acting on conduct problems and hyperactivity emerged at ages 12 and 16, adding to the genetic prediction from age 4. These findings demonstrate that genetic and shared-environmental factors underpinning behavior problems in early childhood predict educational achievement in midadolescence. These findings are consistent with the notion that early-childhood behavior problems reflect the initiation of a life-course persistent trajectory with concomitant implications for social attainment. However, we also find evidence that genetic and nonshared-environment innovations acting on behavior problems have implications for subsequent educational achievement, consistent with recent work arguing that adolescence represents a sensitive period for socioaffective development. © 2016 The Authors. Journal of Child Psychology and Psychiatry published by John Wiley & Sons Ltd on behalf of Association for Child and Adolescent Mental Health.

  13. Defining population structure and genetic signatures of decline in the giant garter snake (Thamnophis gigas): implications for conserving threatened species within highly altered landscapes

    Science.gov (United States)

    Wood, Dustin A.; Halstead, Brian J.; Casazza, Michael L.; Hansen, Eric C.; Wylie, Glenn D.; Vandergast, Amy

    2015-01-01

    Anthropogenic habitat fragmentation can disrupt the ability of species to disperse across landscapes, which can alter the levels and distribution of genetic diversity within populations and negatively impact long-term viability. The giant gartersnake (Thamnophis gigas) is a state and federally threatened species that historically occurred in the wetland habitats of California’s Great Central Valley. Despite the loss of 93 % of historic wetlands throughout the Central Valley, giant gartersnakes continue to persist in relatively small, isolated patches of highly modified agricultural wetlands. Gathering information regarding genetic diversity and effective population size represents an essential component for conservation management programs aimed at this species. Previous mitochondrial sequence studies have revealed historical patterns of differentiation, yet little is known about contemporary population structure and diversity. On the basis of 15 microsatellite loci, we estimate population structure and compare indices of genetic diversity among populations spanning seven drainage basins within the Central Valley. We sought to understand how habitat loss may have affected genetic differentiation, genetic diversity and effective population size, and what these patterns suggest in terms of management and restoration actions. We recovered five genetic clusters that were consistent with regional drainage basins, although three northern basins within the Sacramento Valley formed a single genetic cluster. Our results show that northern drainage basin populations have higher connectivity than among central and southern basins populations, and that greater differentiation exists among the more geographically isolated populations in the central and southern portion of the species’ range. Genetic diversity measures among basins were significantly different, and were generally lower in southern basin populations. Levels of inbreeding and evidence of population

  14. Genome-wide prediction of traits with different genetic architecture through efficient variable selection.

    Science.gov (United States)

    Wimmer, Valentin; Lehermeier, Christina; Albrecht, Theresa; Auinger, Hans-Jürgen; Wang, Yu; Schön, Chris-Carolin

    2013-10-01

    In genome-based prediction there is considerable uncertainty about the statistical model and method required to maximize prediction accuracy. For traits influenced by a small number of quantitative trait loci (QTL), predictions are expected to benefit from methods performing variable selection [e.g., BayesB or the least absolute shrinkage and selection operator (LASSO)] compared to methods distributing effects across the genome [ridge regression best linear unbiased prediction (RR-BLUP)]. We investigate the assumptions underlying successful variable selection by combining computer simulations with large-scale experimental data sets from rice (Oryza sativa L.), wheat (Triticum aestivum L.), and Arabidopsis thaliana (L.). We demonstrate that variable selection can be successful when the number of phenotyped individuals is much larger than the number of causal mutations contributing to the trait. We show that the sample size required for efficient variable selection increases dramatically with decreasing trait heritabilities and increasing extent of linkage disequilibrium (LD). We contrast and discuss contradictory results from simulation and experimental studies with respect to superiority of variable selection methods over RR-BLUP. Our results demonstrate that due to long-range LD, medium heritabilities, and small sample sizes, superiority of variable selection methods cannot be expected in plant breeding populations even for traits like FRIGIDA gene expression in Arabidopsis and flowering time in rice, assumed to be influenced by a few major QTL. We extend our conclusions to the analysis of whole-genome sequence data and infer upper bounds for the number of causal mutations which can be identified by LASSO. Our results have major impact on the choice of statistical method needed to make credible inferences about genetic architecture and prediction accuracy of complex traits.

  15. Paroxysmal atrial fibrillation prediction based on HRV analysis and non-dominated sorting genetic algorithm III.

    Science.gov (United States)

    Boon, K H; Khalil-Hani, M; Malarvili, M B

    2018-01-01

    This paper presents a method that able to predict the paroxysmal atrial fibrillation (PAF). The method uses shorter heart rate variability (HRV) signals when compared to existing methods, and achieves good prediction accuracy. PAF is a common cardiac arrhythmia that increases the health risk of a patient, and the development of an accurate predictor of the onset of PAF is clinical important because it increases the possibility to electrically stabilize and prevent the onset of atrial arrhythmias with different pacing techniques. We propose a multi-objective optimization algorithm based on the non-dominated sorting genetic algorithm III for optimizing the baseline PAF prediction system, that consists of the stages of pre-processing, HRV feature extraction, and support vector machine (SVM) model. The pre-processing stage comprises of heart rate correction, interpolation, and signal detrending. After that, time-domain, frequency-domain, non-linear HRV features are extracted from the pre-processed data in feature extraction stage. Then, these features are used as input to the SVM for predicting the PAF event. The proposed optimization algorithm is used to optimize the parameters and settings of various HRV feature extraction algorithms, select the best feature subsets, and tune the SVM parameters simultaneously for maximum prediction performance. The proposed method achieves an accuracy rate of 87.7%, which significantly outperforms most of the previous works. This accuracy rate is achieved even with the HRV signal length being reduced from the typical 30 min to just 5 min (a reduction of 83%). Furthermore, another significant result is the sensitivity rate, which is considered more important that other performance metrics in this paper, can be improved with the trade-off of lower specificity. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. Prediction of Aerodynamic Coefficient using Genetic Algorithm Optimized Neural Network for Sparse Data

    Science.gov (United States)

    Rajkumar, T.; Bardina, Jorge; Clancy, Daniel (Technical Monitor)

    2002-01-01

    Wind tunnels use scale models to characterize aerodynamic coefficients, Wind tunnel testing can be slow and costly due to high personnel overhead and intensive power utilization. Although manual curve fitting can be done, it is highly efficient to use a neural network to define the complex relationship between variables. Numerical simulation of complex vehicles on the wide range of conditions required for flight simulation requires static and dynamic data. Static data at low Mach numbers and angles of attack may be obtained with simpler Euler codes. Static data of stalled vehicles where zones of flow separation are usually present at higher angles of attack require Navier-Stokes simulations which are costly due to the large processing time required to attain convergence. Preliminary dynamic data may be obtained with simpler methods based on correlations and vortex methods; however, accurate prediction of the dynamic coefficients requires complex and costly numerical simulations. A reliable and fast method of predicting complex aerodynamic coefficients for flight simulation I'S presented using a neural network. The training data for the neural network are derived from numerical simulations and wind-tunnel experiments. The aerodynamic coefficients are modeled as functions of the flow characteristics and the control surfaces of the vehicle. The basic coefficients of lift, drag and pitching moment are expressed as functions of angles of attack and Mach number. The modeled and training aerodynamic coefficients show good agreement. This method shows excellent potential for rapid development of aerodynamic models for flight simulation. Genetic Algorithms (GA) are used to optimize a previously built Artificial Neural Network (ANN) that reliably predicts aerodynamic coefficients. Results indicate that the GA provided an efficient method of optimizing the ANN model to predict aerodynamic coefficients. The reliability of the ANN using the GA includes prediction of aerodynamic

  17. Individualized prediction of schizophrenia based on the whole-brain pattern of altered white matter tract integrity.

    Science.gov (United States)

    Chen, Yu-Jen; Liu, Chih-Min; Hsu, Yung-Chin; Lo, Yu-Chun; Hwang, Tzung-Jeng; Hwu, Hai-Gwo; Lin, Yi-Tin; Tseng, Wen-Yih Isaac

    2018-01-01

    A schizophrenia diagnosis relies on characteristic symptoms identified by trained physicians, and is thus prone to subjectivity. This study developed a procedure for the individualized prediction of schizophrenia based on whole-brain patterns of altered white matter tract integrity. The study comprised training (108 patients and 144 controls) and testing (60 patients and 60 controls) groups. Male and female participants were comparable in each group and were analyzed separately. All participants underwent diffusion spectrum imaging of the head, and the data were analyzed using the tract-based automatic analysis method to generate a standardized two-dimensional array of white matter tract integrity, called the connectogram. Unique patterns in the connectogram that most accurately identified schizophrenia were systematically reviewed in the training group. Then, the diagnostic performance of the patterns was individually verified in the testing group by using receiver-operating characteristic curve analysis. The performance was high in men (accuracy = 0.85) and satisfactory in women (accuracy = 0.75). In men, the pattern was located in discrete fiber tracts, as has been consistently reported in the literature; by contrast, the pattern was widespread over all tracts in women. These distinct patterns suggest that there is a higher variability in the microstructural alterations in female patients than in male patients. The individualized prediction of schizophrenia is feasible based on the different whole-brain patterns of tract integrity. The optimal masks and their corresponding regions in the fiber tracts could serve as potential imaging biomarkers for schizophrenia. Hum Brain Mapp 39:575-587, 2018. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  18. Failing to learn from negative prediction errors: Obesity is associated with alterations in a fundamental neural learning mechanism.

    Science.gov (United States)

    Mathar, David; Neumann, Jane; Villringer, Arno; Horstmann, Annette

    2017-10-01

    Prediction errors (PEs) encode the difference between expected and actual action outcomes in the brain via dopaminergic modulation. Integration of these learning signals ensures efficient behavioral adaptation. Obesity has recently been linked to altered dopaminergic fronto-striatal circuits, thus implying impairments in cognitive domains that rely on its integrity. 28 obese and 30 lean human participants performed an implicit stimulus-response learning paradigm inside an fMRI scanner. Computational modeling and psycho-physiological interaction (PPI) analysis was utilized for assessing PE-related learning and associated functional connectivity. We show that human obesity is associated with insufficient incorporation of negative PEs into behavioral adaptation even in a non-food context, suggesting differences in a fundamental neural learning mechanism. Obese subjects were less efficient in using negative PEs to improve implicit learning performance, despite proper coding of PEs in striatum. We further observed lower functional coupling between ventral striatum and supplementary motor area in obese subjects subsequent to negative PEs. Importantly, strength of functional coupling predicted task performance and negative PE utilization. These findings show that obesity is linked to insufficient behavioral adaptation specifically in response to negative PEs, and to associated alterations in function and connectivity within the fronto-striatal system. Recognition of neural differences as a central characteristic of obesity hopefully paves the way to rethink established intervention strategies: Differential behavioral sensitivity to negative and positive PEs should be considered when designing intervention programs. Measures relying on penalization of unwanted behavior may prove less effective in obese subjects than alternative approaches. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Predictive genetic testing in children: constitutional mismatch repair deficiency cancer predisposing syndrome.

    Science.gov (United States)

    Bruwer, Zandrè; Algar, Ursula; Vorster, Alvera; Fieggen, Karen; Davidson, Alan; Goldberg, Paul; Wainwright, Helen; Ramesar, Rajkumar

    2014-04-01

    Biallelic germline mutations in mismatch repair genes predispose to constitutional mismatch repair deficiency syndrome (CMMR-D). The condition is characterized by a broad spectrum of early-onset tumors, including hematological, brain and bowel and is frequently associated with features of Neurofibromatosis type 1. Few definitive screening recommendations have been suggested and no published reports have described predictive testing. We report on the first case of predictive testing for CMMR-D following the identification of two non-consanguineous parents, with the same heterozygous mutation in MLH1: c.1528C > T. The genetic counseling offered to the family, for their two at-risk daughters, is discussed with a focus on the ethical considerations of testing children for known cancer-causing variants. The challenges that are encountered when reporting on heterozygosity in a child younger than 18 years (disclosure of carrier status and risk for Lynch syndrome), when discovered during testing for homozygosity, are addressed. In addition, the identification of CMMR-D in a three year old, and the recommended clinical surveillance that was proposed for this individual is discussed. Despite predictive testing and presymptomatic screening, the sudden death of the child with CMMR-D syndrome occurred 6 months after her last surveillance MRI. This report further highlights the difficulty of developing guidelines, as a result of the rarity of cases and diversity of presentation.

  20. Prediction of genetic values of quantitative traits in plant breeding using pedigree and molecular markers.

    Science.gov (United States)

    Crossa, José; Campos, Gustavo de Los; Pérez, Paulino; Gianola, Daniel; Burgueño, Juan; Araus, José Luis; Makumbi, Dan; Singh, Ravi P; Dreisigacker, Susanne; Yan, Jianbing; Arief, Vivi; Banziger, Marianne; Braun, Hans-Joachim

    2010-10-01

    The availability of dense molecular markers has made possible the use of genomic selection (GS) for plant breeding. However, the evaluation of models for GS in real plant populations is very limited. This article evaluates the performance of parametric and semiparametric models for GS using wheat (Triticum aestivum L.) and maize (Zea mays) data in which different traits were measured in several environmental conditions. The findings, based on extensive cross-validations, indicate that models including marker information had higher predictive ability than pedigree-based models. In the wheat data set, and relative to a pedigree model, gains in predictive ability due to inclusion of markers ranged from 7.7 to 35.7%. Correlation between observed and predictive values in the maize data set achieved values up to 0.79. Estimates of marker effects were different across environmental conditions, indicating that genotype × environment interaction is an important component of genetic variability. These results indicate that GS in plant breeding can be an effective strategy for selecting among lines whose phenotypes have yet to be observed.

  1. A hybrid genetic algorithm and linear regression for prediction of NOx emission in power generation plant

    International Nuclear Information System (INIS)

    Bunyamin, Muhammad Afif; Yap, Keem Siah; Aziz, Nur Liyana Afiqah Abdul; Tiong, Sheih Kiong; Wong, Shen Yuong; Kamal, Md Fauzan

    2013-01-01

    This paper presents a new approach of gas emission estimation in power generation plant using a hybrid Genetic Algorithm (GA) and Linear Regression (LR) (denoted as GA-LR). The LR is one of the approaches that model the relationship between an output dependant variable, y, with one or more explanatory variables or inputs which denoted as x. It is able to estimate unknown model parameters from inputs data. On the other hand, GA is used to search for the optimal solution until specific criteria is met causing termination. These results include providing good solutions as compared to one optimal solution for complex problems. Thus, GA is widely used as feature selection. By combining the LR and GA (GA-LR), this new technique is able to select the most important input features as well as giving more accurate prediction by minimizing the prediction errors. This new technique is able to produce more consistent of gas emission estimation, which may help in reducing population to the environment. In this paper, the study's interest is focused on nitrous oxides (NOx) prediction. The results of the experiment are encouraging.

  2. The fatigue life prediction of aluminium alloy using genetic algorithm and neural network

    Science.gov (United States)

    Susmikanti, Mike

    2013-09-01

    The behavior of the fatigue life of the industrial materials is very important. In many cases, the material with experiencing fatigue life cannot be avoided, however, there are many ways to control their behavior. Many investigations of the fatigue life phenomena of alloys have been done, but it is high cost and times consuming computation. This paper report the modeling and simulation approaches to predict the fatigue life behavior of Aluminum Alloys and resolves some problems of computation. First, the simulation using genetic algorithm was utilized to optimize the load to obtain the stress values. These results can be used to provide N-cycle fatigue life of the material. Furthermore, the experimental data was applied as input data in the neural network learning, while the samples data were applied for testing of the training data. Finally, the multilayer perceptron algorithm is applied to predict whether the given data sets in accordance with the fatigue life of the alloy. To achieve rapid convergence, the Levenberg-Marquardt algorithm was also employed. The simulations results shows that the fatigue behaviors of aluminum under pressure can be predicted. In addition, implementation of neural networks successfully identified a model for material fatigue life.

  3. Alterations of social interaction through genetic and environmental manipulation of the 22q11.2 gene Sept5 in the mouse brain.

    Science.gov (United States)

    Harper, Kathryn M; Hiramoto, Takeshi; Tanigaki, Kenji; Kang, Gina; Suzuki, Go; Trimble, William; Hiroi, Noboru

    2012-08-01

    Social behavior dysfunction is a symptomatic element of schizophrenia and autism spectrum disorder (ASD). Although altered activities in numerous brain regions are associated with defective social cognition and perception, the causative relationship between these altered activities and social cognition and perception-and their genetic underpinnings-are not known in humans. To address these issues, we took advantage of the link between hemizygous deletion of human chromosome 22q11.2 and high rates of social behavior dysfunction, schizophrenia and ASD. We genetically manipulated Sept5, a 22q11.2 gene, and evaluated its role in social interaction in mice. Sept5 deficiency, against a high degree of homogeneity in a congenic genetic background, selectively impaired active affiliative social interaction in mice. Conversely, virally guided overexpression of Sept5 in the hippocampus or, to a lesser extent, the amygdala elevated levels of active affiliative social interaction in C57BL/6J mice. Congenic knockout mice and mice overexpressing Sept5 in the hippocampus or amygdala were indistinguishable from control mice in novelty and olfactory responses, anxiety or motor activity. Moreover, post-weaning individual housing, an environmental condition designed to reduce stress in male mice, selectively raised levels of Sept5 protein in the amygdala and increased active affiliative social interaction in C57BL/6J mice. These findings identify this 22q11.2 gene in the hippocampus and amygdala as a determinant of social interaction and suggest that defective social interaction seen in 22q11.2-associated schizophrenia and ASD can be genetically and environmentally modified by altering this 22q11.2 gene.

  4. Reconstruction of DNA sequences using genetic algorithms and cellular automata: towards mutation prediction?

    Science.gov (United States)

    Mizas, Ch; Sirakoulis, G Ch; Mardiris, V; Karafyllidis, I; Glykos, N; Sandaltzopoulos, R

    2008-04-01

    Change of DNA sequence that fuels evolution is, to a certain extent, a deterministic process because mutagenesis does not occur in an absolutely random manner. So far, it has not been possible to decipher the rules that govern DNA sequence evolution due to the extreme complexity of the entire process. In our attempt to approach this issue we focus solely on the mechanisms of mutagenesis and deliberately disregard the role of natural selection. Hence, in this analysis, evolution refers to the accumulation of genetic alterations that originate from mutations and are transmitted through generations without being subjected to natural selection. We have developed a software tool that allows modelling of a DNA sequence as a one-dimensional cellular automaton (CA) with four states per cell which correspond to the four DNA bases, i.e. A, C, T and G. The four states are represented by numbers of the quaternary number system. Moreover, we have developed genetic algorithms (GAs) in order to determine the rules of CA evolution that simulate the DNA evolution process. Linear evolution rules were considered and square matrices were used to represent them. If DNA sequences of different evolution steps are available, our approach allows the determination of the underlying evolution rule(s). Conversely, once the evolution rules are deciphered, our tool may reconstruct the DNA sequence in any previous evolution step for which the exact sequence information was unknown. The developed tool may be used to test various parameters that could influence evolution. We describe a paradigm relying on the assumption that mutagenesis is governed by a near-neighbour-dependent mechanism. Based on the satisfactory performance of our system in the deliberately simplified example, we propose that our approach could offer a starting point for future attempts to understand the mechanisms that govern evolution. The developed software is open-source and has a user-friendly graphical input interface.

  5. MYC protein expression and genetic alterations have prognostic impact in patients with diffuse large B-cell lymphoma treated with immunochemotherapy.

    Science.gov (United States)

    Valera, Alexandra; López-Guillermo, Armando; Cardesa-Salzmann, Teresa; Climent, Fina; González-Barca, Eva; Mercadal, Santiago; Espinosa, Iñigo; Novelli, Silvana; Briones, Javier; Mate, José L; Salamero, Olga; Sancho, Juan M; Arenillas, Leonor; Serrano, Sergi; Erill, Nadina; Martínez, Daniel; Castillo, Paola; Rovira, Jordina; Martínez, Antonio; Campo, Elias; Colomo, Luis

    2013-10-01

    MYC alterations influence the survival of patients with diffuse large B-cell lymphoma. Most studies have focused on MYC translocations but there is little information regarding the impact of numerical alterations and protein expression. We analyzed the genetic alterations and protein expression of MYC, BCL2, BCL6, and MALT1 in 219 cases of diffuse large B-cell lymphoma. MYC rearrangement occurred as the sole abnormality (MYC single-hit) in 3% of cases, MYC and concurrent BCL2 and/or BCL6 rearrangements (MYC double/triple-hit) in 4%, MYC amplifications in 2% and MYC gains in 19%. MYC single-hit, MYC double/triple-hit and MYC amplifications, but not MYC gains or other gene rearrangements, were associated with unfavorable progression-free survival and overall survival. MYC protein expression, evaluated using computerized image analysis, captured the unfavorable prognosis of MYC translocations/amplifications and identified an additional subset of patients without gene alterations but with similar poor prognosis. Patients with tumors expressing both MYC/BCL2 had the worst prognosis, whereas those with double-negative tumors had the best outcome. High MYC expression was associated with shorter overall survival irrespectively of the International Prognostic Index and BCL2 expression. In conclusion, MYC protein expression identifies a subset of diffuse large B-cell lymphoma with very poor prognosis independently of gene alterations and other prognostic parameters.

  6. Integrated genetic and epigenetic prediction of coronary heart disease in the Framingham Heart Study.

    Directory of Open Access Journals (Sweden)

    Meeshanthini V Dogan

    Full Text Available An improved method for detecting coronary heart disease (CHD could have substantial clinical impact. Building on the idea that systemic effects of CHD risk factors are a conglomeration of genetic and environmental factors, we use machine learning techniques and integrate genetic, epigenetic and phenotype data from the Framingham Heart Study to build and test a Random Forest classification model for symptomatic CHD. Our classifier was trained on n = 1,545 individuals and consisted of four DNA methylation sites, two SNPs, age and gender. The methylation sites and SNPs were selected during the training phase. The final trained model was then tested on n = 142 individuals. The test data comprised of individuals removed based on relatedness to those in the training dataset. This integrated classifier was capable of classifying symptomatic CHD status of those in the test set with an accuracy, sensitivity and specificity of 78%, 0.75 and 0.80, respectively. In contrast, a model using only conventional CHD risk factors as predictors had an accuracy and sensitivity of only 65% and 0.42, respectively, but with a specificity of 0.89 in the test set. Regression analyses of the methylation signatures illustrate our ability to map these signatures to known risk factors in CHD pathogenesis. These results demonstrate the capability of an integrated approach to effectively model symptomatic CHD status. These results also suggest that future studies of biomaterial collected from longitudinally informative cohorts that are specifically characterized for cardiac disease at follow-up could lead to the introduction of sensitive, readily employable integrated genetic-epigenetic algorithms for predicting onset of future symptomatic CHD.

  7. Genetic variations altering FSH action affect circulating hormone levels as well as follicle growth in healthy peripubertal girls.

    Science.gov (United States)

    Busch, Alexander S; Hagen, Casper P; Almstrup, Kristian; Main, Katharina M; Juul, Anders

    2016-04-01

    Do variants of the genes encoding follicle stimulating hormone (FSH) beta subunit (B) and FSH receptor (R) impact circulating reproductive hormone levels and ovarian follicle maturation in healthy peripubertal girls? FSHB and FSHR genetic variants exert, alone or their combination, distinct effects on reproductive hormone levels as well as ovarian follicle maturation in healthy peripubertal girls. FSHB and FSHR genetic variants impact reproductive hormone levels as well as associated pathologies in women. While FSHR c. 2039A>G is known to alter gonadotrophin levels in women, FSHR c.-29G>A has not yet been shown to exert effect and there are conflicting results concerning FSHB c.-211G>T. This population-based study included 633 girls recruited as part of two cohorts, the COPENHAGEN Puberty Study (2006-2014, a cross-sectional and ongoing longitudinal study) and the Copenhagen Mother-Child Cohort (1997-2002, including transabdominal ultrasound (TAUS) of the ovaries in a subset of 91 peripubertal girls). Clinical examinations, including pubertal breast stage (Tanner's classification B1-B5) were performed. Circulating levels of FSH, luteinizing hormone (LH), estradiol, anti-Mullerian hormone (AMH) and inhibin-B were assessed by immunoassays. In a subset of the girls (n = 91), ovarian volume and the number/size of antral follicles were assessed by TAUS. Genotypes were determined by competitive PCR. FSHR c.2039A>G minor alleles were positively associated with serum FSH (β = 0.08, P = 0.004), LH (β = 0.06, P = 0.012) and estradiol (β = 0.06, P = 0.017) (adjusted for Tanner stages). In a combined model, FSHR c.-29G>A and FSHR c.2039A>G alleles were positively associated with FSH levels in early-pubertal girls (B2 + B3, n = 327, r = 0.1, P = 0.02) and in young adolescents (B4 + B5, n = 149, r = 0.2, P = 0.01). Serum AMH and inhibin B levels were not significantly influenced by the single nucleotide polymorphisms (SNPs). Single SNPs were not associated with follicles

  8. Comparison of genetic algorithm and imperialist competitive algorithms in predicting bed load transport in clean pipe.

    Science.gov (United States)

    Ebtehaj, Isa; Bonakdari, Hossein

    2014-01-01

    The existence of sediments in wastewater greatly affects the performance of the sewer and wastewater transmission systems. Increased sedimentation in wastewater collection systems causes problems such as reduced transmission capacity and early combined sewer overflow. The article reviews the performance of the genetic algorithm (GA) and imperialist competitive algorithm (ICA) in minimizing the target function (mean square error of observed and predicted Froude number). To study the impact of bed load transport parameters, using four non-dimensional groups, six different models have been presented. Moreover, the roulette wheel selection method is used to select the parents. The ICA with root mean square error (RMSE) = 0.007, mean absolute percentage error (MAPE) = 3.5% show better results than GA (RMSE = 0.007, MAPE = 5.6%) for the selected model. All six models return better results than the GA. Also, the results of these two algorithms were compared with multi-layer perceptron and existing equations.

  9. Design of artificial neural networks using a genetic algorithm to predict collection efficiency in venturi scrubbers.

    Science.gov (United States)

    Taheri, Mahboobeh; Mohebbi, Ali

    2008-08-30

    In this study, a new approach for the auto-design of neural networks, based on a genetic algorithm (GA), has been used to predict collection efficiency in venturi scrubbers. The experimental input data, including particle diameter, throat gas velocity, liquid to gas flow rate ratio, throat hydraulic diameter, pressure drop across the venturi scrubber and collection efficiency as an output, have been used to create a GA-artificial neural network (ANN) model. The testing results from the model are in good agreement with the experimental data. Comparison of the results of the GA optimized ANN model with the results from the trial-and-error calibrated ANN model indicates that the GA-ANN model is more efficient. Finally, the effects of operating parameters such as liquid to gas flow rate ratio, throat gas velocity, and particle diameter on collection efficiency were determined.

  10. Evaluation of Penalized and Nonpenalized Methods for Disease Prediction with Large-Scale Genetic Data

    Directory of Open Access Journals (Sweden)

    Sungho Won

    2015-01-01

    Full Text Available Owing to recent improvement of genotyping technology, large-scale genetic data can be utilized to identify disease susceptibility loci and this successful finding has substantially improved our understanding of complex diseases. However, in spite of these successes, most of the genetic effects for many complex diseases were found to be very small, which have been a big hurdle to build disease prediction model. Recently, many statistical methods based on penalized regressions have been proposed to tackle the so-called “large P and small N” problem. Penalized regressions including least absolute selection and shrinkage operator (LASSO and ridge regression limit the space of parameters, and this constraint enables the estimation of effects for very large number of SNPs. Various extensions have been suggested, and, in this report, we compare their accuracy by applying them to several complex diseases. Our results show that penalized regressions are usually robust and provide better accuracy than the existing methods for at least diseases under consideration.

  11. Recombination in diverse maize is stable, predictable, and associated with genetic load.

    Science.gov (United States)

    Rodgers-Melnick, Eli; Bradbury, Peter J; Elshire, Robert J; Glaubitz, Jeffrey C; Acharya, Charlotte B; Mitchell, Sharon E; Li, Chunhui; Li, Yongxiang; Buckler, Edward S

    2015-03-24

    Among the fundamental evolutionary forces, recombination arguably has the largest impact on the practical work of plant breeders. Varying over 1,000-fold across the maize genome, the local meiotic recombination rate limits the resolving power of quantitative trait mapping and the precision of favorable allele introgression. The consequences of low recombination also theoretically extend to the species-wide scale by decreasing the power of selection relative to genetic drift, and thereby hindering the purging of deleterious mutations. In this study, we used genotyping-by-sequencing (GBS) to identify 136,000 recombination breakpoints at high resolution within US and Chinese maize nested association mapping populations. We find that the pattern of cross-overs is highly predictable on the broad scale, following the distribution of gene density and CpG methylation. Several large inversions also suppress recombination in distinct regions of several families. We also identify recombination hotspots ranging in size from 1 kb to 30 kb. We find these hotspots to be historically stable and, compared with similar regions with low recombination, to have strongly differentiated patterns of DNA methylation and GC content. We also provide evidence for the historical action of GC-biased gene conversion in recombination hotspots. Finally, using genomic evolutionary rate profiling (GERP) to identify putative deleterious polymorphisms, we find evidence for reduced genetic load in hotspot regions, a phenomenon that may have considerable practical importance for breeding programs worldwide.

  12. Performance of genetic risk factors in prediction of trichloroethylene induced hypersensitivity syndrome.

    Science.gov (United States)

    Dai, Yufei; Chen, Ying; Huang, Hanlin; Zhou, Wei; Niu, Yong; Zhang, Mingrong; Bin, Ping; Dong, Haiyan; Jia, Qiang; Huang, Jianxun; Yi, Juan; Liao, Qijun; Li, Haishan; Teng, Yanxia; Zang, Dan; Zhai, Qingfeng; Duan, Huawei; Shen, Juan; He, Jiaxi; Meng, Tao; Sha, Yan; Shen, Meili; Ye, Meng; Jia, Xiaowei; Xiang, Yingping; Huang, Huiping; Wu, Qifeng; Shi, Mingming; Huang, Xianqing; Yang, Huanming; Luo, Longhai; Li, Sai; Li, Lin; Zhao, Jinyang; Li, Laiyu; Wang, Jun; Zheng, Yuxin

    2015-07-20

    Trichloroethylene induced hypersensitivity syndrome is dose-independent and potentially life threatening disease, which has become one of the serious occupational health issues and requires intensive treatment. To discover the genetic risk factors and evaluate the performance of risk prediction model for the disease, we conducted genomewide association study and replication study with total of 174 cases and 1761 trichloroethylene-tolerant controls. Fifty seven SNPs that exceeded the threshold for genome-wide significance (P < 5 × 10(-8)) were screened to relate with the disease, among which two independent SNPs were identified, that is rs2857281 at MICA (odds ratio, 11.92; P meta = 1.33 × 10(-37)) and rs2523557 between HLA-B and MICA (odds ratio, 7.33; P meta = 8.79 × 10(-35)). The genetic risk score with these two SNPs explains at least 20.9% of the disease variance and up to 32.5-fold variation in inter-individual risk. Combining of two SNPs as predictors for the disease would have accuracy of 80.73%, the area under receiver operator characteristic curves (AUC) scores was 0.82 with sensitivity of 74% and specificity of 85%, which was considered to have excellent discrimination for the disease, and could be considered for translational application for screening employees before exposure.

  13. A Rule-Based Model for Bankruptcy Prediction Based on an Improved Genetic Ant Colony Algorithm

    Directory of Open Access Journals (Sweden)

    Yudong Zhang

    2013-01-01

    Full Text Available In this paper, we proposed a hybrid system to predict corporate bankruptcy. The whole procedure consists of the following four stages: first, sequential forward selection was used to extract the most important features; second, a rule-based model was chosen to fit the given dataset since it can present physical meaning; third, a genetic ant colony algorithm (GACA was introduced; the fitness scaling strategy and the chaotic operator were incorporated with GACA, forming a new algorithm—fitness-scaling chaotic GACA (FSCGACA, which was used to seek the optimal parameters of the rule-based model; and finally, the stratified K-fold cross-validation technique was used to enhance the generalization of the model. Simulation experiments of 1000 corporations’ data collected from 2006 to 2009 demonstrated that the proposed model was effective. It selected the 5 most important factors as “net income to stock broker’s equality,” “quick ratio,” “retained earnings to total assets,” “stockholders’ equity to total assets,” and “financial expenses to sales.” The total misclassification error of the proposed FSCGACA was only 7.9%, exceeding the results of genetic algorithm (GA, ant colony algorithm (ACA, and GACA. The average computation time of the model is 2.02 s.

  14. Prediction of breast cancer risk based on common genetic variants in women of East Asian ancestry.

    Science.gov (United States)

    Wen, Wanqing; Shu, Xiao-Ou; Guo, Xingyi; Cai, Qiuyin; Long, Jirong; Bolla, Manjeet K; Michailidou, Kyriaki; Dennis, Joe; Wang, Qin; Gao, Yu-Tang; Zheng, Ying; Dunning, Alison M; García-Closas, Montserrat; Brennan, Paul; Chen, Shou-Tung; Choi, Ji-Yeob; Hartman, Mikael; Ito, Hidemi; Lophatananon, Artitaya; Matsuo, Keitaro; Miao, Hui; Muir, Kenneth; Sangrajrang, Suleeporn; Shen, Chen-Yang; Teo, Soo H; Tseng, Chiu-Chen; Wu, Anna H; Yip, Cheng Har; Simard, Jacques; Pharoah, Paul D P; Hall, Per; Kang, Daehee; Xiang, Yongbing; Easton, Douglas F; Zheng, Wei

    2016-12-08

    Approximately 100 common breast cancer susceptibility alleles have been identified in genome-wide association studies (GWAS). The utility of these variants in breast cancer risk prediction models has not been evaluated adequately in women of Asian ancestry. We evaluated 88 breast cancer risk variants that were identified previously by GWAS in 11,760 cases and 11,612 controls of Asian ancestry. SNPs confirmed to be associated with breast cancer risk in Asian women were used to construct a polygenic risk score (PRS). The relative and absolute risks of breast cancer by the PRS percentiles were estimated based on the PRS distribution, and were used to stratify women into different levels of breast cancer risk. We confirmed significant associations with breast cancer risk for SNPs in 44 of the 78 previously reported loci at P women in the middle quintile of the PRS, women in the top 1% group had a 2.70-fold elevated risk of breast cancer (95% CI: 2.15-3.40). The risk prediction model with the PRS had an area under the receiver operating characteristic curve of 0.606. The lifetime risk of breast cancer for Shanghai Chinese women in the lowest and highest 1% of the PRS was 1.35% and 10.06%, respectively. Approximately one-half of GWAS-identified breast cancer risk variants can be directly replicated in East Asian women. Collectively, common genetic variants are important predictors for breast cancer risk. Using common genetic variants for breast cancer could help identify women at high risk of breast cancer.

  15. Genetic programming based quantitative structure-retention relationships for the prediction of Kovats retention indices.

    Science.gov (United States)

    Goel, Purva; Bapat, Sanket; Vyas, Renu; Tambe, Amruta; Tambe, Sanjeev S

    2015-11-13

    The development of quantitative structure-retention relationships (QSRR) aims at constructing an appropriate linear/nonlinear model for the prediction of the retention behavior (such as Kovats retention index) of a solute on a chromatographic column. Commonly, multi-linear regression and artificial neural networks are used in the QSRR development in the gas chromatography (GC). In this study, an artificial intelligence based data-driven modeling formalism, namely genetic programming (GP), has been introduced for the development of quantitative structure based models predicting Kovats retention indices (KRI). The novelty of the GP formalism is that given an example dataset, it searches and optimizes both the form (structure) and the parameters of an appropriate linear/nonlinear data-fitting model. Thus, it is not necessary to pre-specify the form of the data-fitting model in the GP-based modeling. These models are also less complex, simple to understand, and easy to deploy. The effectiveness of GP in constructing QSRRs has been demonstrated by developing models predicting KRIs of light hydrocarbons (case study-I) and adamantane derivatives (case study-II). In each case study, two-, three- and four-descriptor models have been developed using the KRI data available in the literature. The results of these studies clearly indicate that the GP-based models possess an excellent KRI prediction accuracy and generalization capability. Specifically, the best performing four-descriptor models in both the case studies have yielded high (>0.9) values of the coefficient of determination (R(2)) and low values of root mean squared error (RMSE) and mean absolute percent error (MAPE) for training, test and validation set data. The characteristic feature of this study is that it introduces a practical and an effective GP-based method for developing QSRRs in gas chromatography that can be gainfully utilized for developing other types of data-driven models in chromatography science

  16. PANTHER-PSEP: predicting disease-causing genetic variants using position-specific evolutionary preservation.

    Science.gov (United States)

    Tang, Haiming; Thomas, Paul D

    2016-07-15

    PANTHER-PSEP is a new software tool for predicting non-synonymous genetic variants that may play a causal role in human disease. Several previous variant pathogenicity prediction methods have been proposed that quantify evolutionary conservation among homologous proteins from different organisms. PANTHER-PSEP employs a related but distinct metric based on 'evolutionary preservation': homologous proteins are used to reconstruct the likely sequences of ancestral proteins at nodes in a phylogenetic tree, and the history of each amino acid can be traced back in time from its current state to estimate how long that state has been preserved in its ancestors. Here, we describe the PSEP tool, and assess its performance on standard benchmarks for distinguishing disease-associated from neutral variation in humans. On these benchmarks, PSEP outperforms not only previous tools that utilize evolutionary conservation, but also several highly used tools that include multiple other sources of information as well. For predicting pathogenic human variants, the trace back of course starts with a human 'reference' protein sequence, but the PSEP tool can also be applied to predicting deleterious or pathogenic variants in reference proteins from any of the ∼100 other species in the PANTHER database. PANTHER-PSEP is freely available on the web at http://pantherdb.org/tools/csnpScoreForm.jsp Users can also download the command-line based tool at ftp://ftp.pantherdb.org/cSNP_analysis/PSEP/ CONTACT: pdthomas@usc.edu 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.

  17. Short communication: Genetic study of methane production predicted from milk fat composition in dairy cows.

    Science.gov (United States)

    van Engelen, S; Bovenhuis, H; Dijkstra, J; van Arendonk, J A M; Visker, M H P W

    2015-11-01

    Dairy cows produce enteric methane, a greenhouse gas with 25 times the global warming potential of CO2. Breeding could make a permanent, cumulative, and long-term contribution to methane reduction. Due to a lack of accurate, repeatable, individual methane measurements needed for breeding, indicators of methane production based on milk fatty acids have been proposed. The aim of the present study was to quantify the genetic variation for predicted methane yields. The milk fat composition of 1,905 first-lactation Dutch Holstein-Friesian cows was used to investigate 3 different predicted methane yields (g/kg of DMI): Methane1, Methane2, and Methane3. Methane1 was based on the milk fat proportions of C17:0anteiso, C18:1 rans-10+11, C18:1 cis-11, and C18:1 cis-13 (R(2)=0.73). Methane2 was based on C4:0, C18:0, C18:1 trans-10+11, and C18:1 cis-11 (R(2)=0.70). Methane3 was based on C4:0, C6:0, and C18:1 trans-10+11 (R(2)=0.63). Predicted methane yields were demonstrated to be heritable traits, with heritabilities between 0.12 and 0.44. Breeding can, thus, be used to decrease methane production predicted based on milk fatty acids. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  18. Linear reaction norm models for genetic merit prediction of Angus cattle under genotype by environment interaction.

    Science.gov (United States)

    Cardoso, F F; Tempelman, R J

    2012-07-01

    The objectives of this work were to assess alternative linear reaction norm (RN) models for genetic evaluation of Angus cattle in Brazil. That is, we investigated the interaction between genotypes and continuous descriptors of the environmental variation to examine evidence of genotype by environment interaction (G×E) in post-weaning BW gain (PWG) and to compare the environmental sensitivity of national and imported Angus sires. Data were collected by the Brazilian Angus Improvement Program from 1974 to 2005 and consisted of 63,098 records and a pedigree file with 95,896 animals. Six models were implemented using Bayesian inference and compared using the Deviance Information Criterion (DIC). The simplest model was M(1), a traditional animal model, which showed the largest DIC and hence the poorest fit when compared with the 4 alternative RN specifications accounting for G×E. In M(2), a 2-step procedure was implemented using the contemporary group posterior means of M(1) as the environmental gradient, ranging from -92.6 to +265.5 kg. Moreover, the benefits of jointly estimating all parameters in a 1-step approach were demonstrated by M(3). Additionally, we extended M(3) to allow for residual heteroskedasticity using an exponential function (M(4)) and the best fitting (smallest DIC) environmental classification model (M(5)) specification. Finally, M(6) added just heteroskedastic residual variance to M(1). Heritabilities were less at harsh environments and increased with the improvement of production conditions for all RN models. Rank correlations among genetic merit predictions obtained by M(1) and by the best fitting RN models M(3) (homoskedastic) and M(5) (heteroskedastic) at different environmental levels ranged from 0.79 and 0.81, suggesting biological importance of G×E in Brazilian Angus PWG. These results suggest that selection progress could be optimized by adopting environment-specific genetic merit predictions. The PWG environmental sensitivity of

  19. Recent and projected increases in atmospheric CO2 concentration can enhance gene flow between wild and genetically altered rice (Oryza sativa).

    Science.gov (United States)

    Ziska, Lewis H; Gealy, David R; Tomecek, Martha B; Jackson, Aaron K; Black, Howard L

    2012-01-01

    Although recent and projected increases in atmospheric carbon dioxide can alter plant phenological development, these changes have not been quantified in terms of floral outcrossing rates or gene transfer. Could differential phenological development in response to rising CO(2) between genetically modified crops and wild, weedy relatives increase the spread of novel genes, potentially altering evolutionary fitness? Here we show that increasing CO(2) from an early 20(th) century concentration (300 µmol mol(-1)) to current (400 µmol mol(-1)) and projected, mid-21(st) century (600 µmol mol(-1)) values, enhanced the flow of genes from wild, weedy rice to the genetically altered, herbicide resistant, cultivated population, with outcrossing increasing from 0.22% to 0.71% from 300 to 600 µmol mol(-1). The increase in outcrossing and gene transfer was associated with differential increases in plant height, as well as greater tiller and panicle production in the wild, relative to the cultivated population. In addition, increasing CO(2) also resulted in a greater synchronicity in flowering times between the two populations. The observed changes reported here resulted in a subsequent increase in rice dedomestication and a greater number of weedy, herbicide-resistant hybrid progeny. Overall, these data suggest that differential phenological responses to rising atmospheric CO(2) could result in enhanced flow of novel genes and greater success of feral plant species in agroecosystems.

  20. Recent and projected increases in atmospheric CO2 concentration can enhance gene flow between wild and genetically altered rice (Oryza sativa.

    Directory of Open Access Journals (Sweden)

    Lewis H Ziska

    Full Text Available Although recent and projected increases in atmospheric carbon dioxide can alter plant phenological development, these changes have not been quantified in terms of floral outcrossing rates or gene transfer. Could differential phenological development in response to rising CO(2 between genetically modified crops and wild, weedy relatives increase the spread of novel genes, potentially altering evolutionary fitness? Here we show that increasing CO(2 from an early 20(th century concentration (300 µmol mol(-1 to current (400 µmol mol(-1 and projected, mid-21(st century (600 µmol mol(-1 values, enhanced the flow of genes from wild, weedy rice to the genetically altered, herbicide resistant, cultivated population, with outcrossing increasing from 0.22% to 0.71% from 300 to 600 µmol mol(-1. The increase in outcrossing and gene transfer was associated with differential increases in plant height, as well as greater tiller and panicle production in the wild, relative to the cultivated population. In addition, increasing CO(2 also resulted in a greater synchronicity in flowering times between the two populations. The observed changes reported here resulted in a subsequent increase in rice dedomestication and a greater number of weedy, herbicide-resistant hybrid progeny. Overall, these data suggest that differential phenological responses to rising atmospheric CO(2 could result in enhanced flow of novel genes and greater success of feral plant species in agroecosystems.

  1. VHL genetic alteration in CCRCC does not determine de-regulation of HIF, CAIX, hnRNP A2/B1 and osteopontin.

    LENUS (Irish Health Repository)

    Nyhan, Michelle J

    2012-01-31

    BACKGROUND: von Hippel-Lindau (VHL) tumour suppressor gene inactivation is associated with clear cell renal cell carcinoma (CCRCC) development. The VHL protein (pVHL) has been proposed to regulate the expression of several proteins including Hypoxia Inducible Factor-alpha (HIF-alpha), carbonic anhydrase (CA)IX, heterogeneous nuclear ribonucleoprotein (hnRNP) A2\\/B1 and osteopontin. pVHL has been characterized in vitro, however, clinical studies are limited. We evaluated the impact of VHL genetic alterations on the expression of several pVHL protein targets in paired normal and tumor tissue. METHODS: The VHL gene was sequenced in 23 CCRCC patients and VHL transcript levels were evaluated by real-time RT-PCR. Expression of pVHL\\'s protein targets were determined by Western blotting in 17 paired patient samples. RESULTS: VHL genetic alterations were identified in 43.5% (10\\/23) of CCRCCs. HIF-1alpha, HIF-2alpha and CAIX were up-regulated in 88.2% (15\\/17), 100% (17\\/17) and 88.2% (15\\/17) of tumors respectively and their expression is independent of VHL status. hnRNP A2\\/B1 and osteopontin expression was variable in CCRCCs and had no association with VHL genetic status. CONCLUSION: As expression of these proposed pVHL targets can be achieved independently of VHL mutation (and possibly by hypoxia alone), these data suggests that other pVHL targets may be more crucial in renal carcinogenesis.

  2. Prediction of Endocrine System Affectation in Fisher 344 Rats by Food Intake Exposed with Malathion, Applying Naïve Bayes Classifier and Genetic Algorithms.

    Science.gov (United States)

    Mora, Juan David Sandino; Hurtado, Darío Amaya; Sandoval, Olga Lucía Ramos

    2016-01-01

    Reported cases of uncontrolled use of pesticides and its produced effects by direct or indirect exposition, represent a high risk for human health. Therefore, in this paper, it is shown the results of the development and execution of an algorithm that predicts the possible effects in endocrine system in Fisher 344 (F344) rats, occasioned by ingestion of malathion. It was referred to ToxRefDB database in which different case studies in F344 rats exposed to malathion were collected. The experimental data were processed using Naïve Bayes (NB) machine learning classifier, which was subsequently optimized using genetic algorithms (GAs). The model was executed in an application with a graphical user interface programmed in C#. There was a tendency to suffer bigger alterations, increasing levels in the parathyroid gland in dosages between 4 and 5 mg/kg/day, in contrast to the thyroid gland for doses between 739 and 868 mg/kg/day. It was showed a greater resistance for females to contract effects on the endocrine system by the ingestion of malathion. Females were more susceptible to suffer alterations in the pituitary gland with exposure times between 3 and 6 months. The prediction model based on NB classifiers allowed to analyze all the possible combinations of the studied variables and improving its accuracy using GAs. Excepting the pituitary gland, females demonstrated better resistance to contract effects by increasing levels on the rest of endocrine system glands.

  3. Monoamine Oxidase-A Genetic Variants and Childhood Abuse Predict Impulsiveness in Borderline Personality Disorder.

    Science.gov (United States)

    Kolla, Nathan J; Meyer, Jeffrey; Sanches, Marcos; Charbonneau, James

    2017-11-30

    Impulsivity is a core feature of borderline personality disorder (BPD) and antisocial personality disorder (ASPD) that likely arises from combined genetic and environmental influences. The interaction of the low activity variant of the monoamine oxidase-A (MAOA-L) gene and early childhood adversity has been shown to predict aggression in clinical and non-clinical populations. Although impulsivity is a risk factor for aggression in BPD and ASPD, little research has investigated potential gene-environment (G×E) influences impacting its expression in these conditions. Moreover, G×E interactions may differ by diagnosis. Full factorial analysis of variance was employed to investigate the influence of monoamine oxidase-A (MAO-A) genotype, childhood abuse, and diagnosis on Barratt Impulsiveness Scale-11 (BIS-11) scores in 61 individuals: 20 subjects with BPD, 18 subjects with ASPD, and 23 healthy controls. A group×genotype×abuse interaction was present (F(2,49)=4.4, p =0.018), such that the interaction of MAOA-L and childhood abuse predicted greater BIS-11 motor impulsiveness in BPD. Additionally, BPD subjects reported higher BIS-11 attentional impulsiveness versus ASPD participants (t(1,36)=2.3, p =0.025). These preliminary results suggest that MAOA-L may modulate the impact of childhood abuse on impulsivity in BPD. Results additionally indicate that impulsiveness may be expressed differently in BPD and ASPD.

  4. Prediction and optimization of thinning in automotive sealing cover using Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Ganesh M. Kakandikar

    2016-01-01

    Full Text Available Deep drawing is a forming process in which a blank of sheet metal is radially drawn into a forming die by the mechanical action of a punch and converted to required shape. Deep drawing involves complex material flow conditions and force distributions. Radial drawing stresses and tangential compressive stresses are induced in flange region due to the material retention property. These compressive stresses result in wrinkling phenomenon in flange region. Normally blank holder is applied for restricting wrinkles. Tensile stresses in radial direction initiate thinning in the wall region of cup. The thinning results into cracking or fracture. The finite element method is widely applied worldwide to simulate the deep drawing process. For real-life simulations of deep drawing process an accurate numerical model, as well as an accurate description of material behavior and contact conditions, is necessary. The finite element method is a powerful tool to predict material thinning deformations before prototypes are made. The proposed innovative methodology combines two techniques for prediction and optimization of thinning in automotive sealing cover. Taguchi design of experiments and analysis of variance has been applied to analyze the influencing process parameters on Thinning. Mathematical relations have been developed to correlate input process parameters and Thinning. Optimization problem has been formulated for thinning and Genetic Algorithm has been applied for optimization. Experimental validation of results proves the applicability of newly proposed approach. The optimized component when manufactured is observed to be safe, no thinning or fracture is observed.

  5. Landscape genetics as a tool for conservation planning: predicting the effects of landscape change on gene flow.

    Science.gov (United States)

    van Strien, Maarten J; Keller, Daniela; Holderegger, Rolf; Ghazoul, Jaboury; Kienast, Felix; Bolliger, Janine

    2014-03-01

    For conservation managers, it is important to know whether landscape changes lead to increasing or decreasing gene flow. Although the discipline of landscape genetics assesses the influence of landscape elements on gene flow, no studies have yet used landscape-genetic models to predict gene flow resulting from landscape change. A species that has already been severely affected by landscape change is the large marsh grasshopper (Stethophyma grossum), which inhabits moist areas in fragmented agricultural landscapes in Switzerland. From transects drawn between all population pairs within maximum dispersal distance (landscape composition as well as some measures of habitat configuration. Additionally, a complete sampling of all populations in our study area allowed incorporating measures of population topology. These measures together with the landscape metrics formed the predictor variables in linear models with gene flow as response variable (F(ST) and mean pairwise assignment probability). With a modified leave-one-out cross-validation approach, we selected the model with the highest predictive accuracy. With this model, we predicted gene flow under several landscape-change scenarios, which simulated construction, rezoning or restoration projects, and the establishment of a new population. For some landscape-change scenarios, significant increase or decrease in gene flow was predicted, while for others little change was forecast. Furthermore, we found that the measures of population topology strongly increase model fit in landscape genetic analysis. This study demonstrates the use of predictive landscape-genetic models in conservation and landscape planning.

  6. Rapid Genetic and Epigenetic Alterations under Intergeneric Genomic Shock in Newly Synthesized Chrysanthemum morifolium × Leucanthemum paludosum Hybrids (Asteraceae)

    Science.gov (United States)

    Wang, Haibin; Jiang, Jiafu; Chen, Sumei; Qi, Xiangyu; Fang, Weimin; Guan, Zhiyong; Teng, Nianjun; Liao, Yuan; Chen, Fadi

    2014-01-01

    The Asteraceae family is at the forefront of the evolution due to frequent hybridization. Hybridization is associated with the induction of widespread genetic and epigenetic changes and has played an important role in the evolution of many plant taxa. We attempted the intergeneric cross Chrysanthemum morifolium × Leucanthemum paludosum. To obtain the success in cross, we have to turn to ovule rescue. DNA profiling of the amphihaploid and amphidiploid was investigated using amplified fragment length polymorphism, sequence-related amplified polymorphism, start codon targeted polymorphism, and methylation-sensitive amplification polymorphism (MSAP). Hybridization induced rapid changes at the genetic and the epigenetic levels. The genetic changes mainly involved loss of parental fragments and gaining of novel fragments, and some eliminated sequences possibly from the noncoding region of L. paludosum. The MSAP analysis indicated that the level of DNA methylation was lower in the amphiploid (∼45%) than in the parental lines (51.5–50.6%), whereas it increased after amphidiploid formation. Events associated with intergeneric genomic shock were a feature of C. morifolium × L. paludosum hybrid, given that the genetic relationship between the parental species is relatively distant. Our results provide genetic and epigenetic evidence for understanding genomic shock in wide crosses between species in Asteraceae and suggest a need to expand our current evolutionary framework to encompass a genetic/epigenetic dimension when seeking to understand wide crosses. PMID:24407856

  7. Rapid genetic and epigenetic alterations under intergeneric genomic shock in newly synthesized Chrysanthemum morifolium x Leucanthemum paludosum hybrids (Asteraceae).

    Science.gov (United States)

    Wang, Haibin; Jiang, Jiafu; Chen, Sumei; Qi, Xiangyu; Fang, Weimin; Guan, Zhiyong; Teng, Nianjun; Liao, Yuan; Chen, Fadi

    2014-01-01

    The Asteraceae family is at the forefront of the evolution due to frequent hybridization. Hybridization is associated with the induction of widespread genetic and epigenetic changes and has played an important role in the evolution of many plant taxa. We attempted the intergeneric cross Chrysanthemum morifolium × Leucanthemum paludosum. To obtain the success in cross, we have to turn to ovule rescue. DNA profiling of the amphihaploid and amphidiploid was investigated using amplified fragment length polymorphism, sequence-related amplified polymorphism, start codon targeted polymorphism, and methylation-sensitive amplification polymorphism (MSAP). Hybridization induced rapid changes at the genetic and the epigenetic levels. The genetic changes mainly involved loss of parental fragments and gaining of novel fragments, and some eliminated sequences possibly from the noncoding region of L. paludosum. The MSAP analysis indicated that the level of DNA methylation was lower in the amphiploid (∼45%) than in the parental lines (51.5-50.6%), whereas it increased after amphidiploid formation. Events associated with intergeneric genomic shock were a feature of C. morifolium × L. paludosum hybrid, given that the genetic relationship between the parental species is relatively distant. Our results provide genetic and epigenetic evidence for understanding genomic shock in wide crosses between species in Asteraceae and suggest a need to expand our current evolutionary framework to encompass a genetic/epigenetic dimension when seeking to understand wide crosses.

  8. Common genetic markers and prediction of recurrent events after ischemic stroke in young adults.

    Science.gov (United States)

    Pezzini, A; Grassi, M; Del Zotto, E; Lodigiani, C; Ferrazzi, P; Spalloni, A; Patella, R; Giossi, A; Volonghi, I; Iacoviello, L; Magoni, M; Rota, L L; Rasura, M; Padovani, A

    2009-09-01

    Scarce information is available on the usefulness of new prediction markers for identifying young ischemic stroke patients at highest risk of recurrence. The predictive effect of traditional risk factors as well as of the 20210A variant of prothrombin gene, the 1691A variant of factor V gene, and the TT677 genotype of the methylenetetrahydrofolate reductase (MTHFR) gene on the risk of recurrence was investigated in a hospital-based cohort study of 511 ischemic stroke patients younger than 45 years followed up for a mean of 43.4 months. Outcome measures were fatal/nonfatal myocardial infarction, ischemic stroke, or TIA. Risk prediction was assessed with the use of the concordance c (c index), and the Net Reclassification Improvement (NRI). The risk of recurrence increased with increasing number of traditional factors (hazard ratio [HR] 2.29, 95% confidence interval [CI] 1.57-3.35 for subjects with 1 factor: HR 5.25, 95% CI 2.45-11.2 for subjects with 2), as well as with that of predisposing genotypes (HR 1.96, 95% CI 1.33-2.89 for subjects carrying 1 at-risk genotype; HR 3.83, 95% CI 1.76-8.34 for those carrying 2). The c statistics increased significantly when the genotypes were included into a model with traditional risk factors (0.696 vs 0.635, test z = 2.41). The NRI was also significant (NRI = 0.172, test z = 2.17). Addition of common genetic variants to traditional risk factors may be an effective method for discriminating young stroke patients at different risk of future ischemic events.

  9. Genetically determined measures of striatal D2 signaling predict prefrontal activity during working memory performance.

    Science.gov (United States)

    Bertolino, Alessandro; Taurisano, Paolo; Pisciotta, Nicola Marco; Blasi, Giuseppe; Fazio, Leonardo; Romano, Raffaella; Gelao, Barbara; Lo Bianco, Luciana; Lozupone, Madia; Di Giorgio, Annabella; Caforio, Grazia; Sambataro, Fabio; Niccoli-Asabella, Artor; Papp, Audrey; Ursini, Gianluca; Sinibaldi, Lorenzo; Popolizio, Teresa; Sadee, Wolfgang; Rubini, Giuseppe

    2010-02-22

    Variation of the gene coding for D2 receptors (DRD2) has been associated with risk for schizophrenia and with working memory deficits. A functional intronic SNP (rs1076560) predicts relative expression of the two D2 receptors isoforms, D2S (mainly pre-synaptic) and D2L (mainly post-synaptic). However, the effect of functional genetic variation of DRD2 on striatal dopamine D2 signaling and on its correlation with prefrontal activity during working memory in humans is not known. Thirty-seven healthy subjects were genotyped for rs1076560 (G>T) and underwent SPECT with [123I]IBZM (which binds primarily to post-synaptic D2 receptors) and with [123I]FP-CIT (which binds to pre-synaptic dopamine transporters, whose activity and density is also regulated by pre-synaptic D2 receptors), as well as BOLD fMRI during N-Back working memory. Subjects carrying the T allele (previously associated with reduced D2S expression) had striatal reductions of [123I]IBZM and of [123I]FP-CIT binding. DRD2 genotype also differentially predicted the correlation between striatal dopamine D2 signaling (as identified with factor analysis of the two radiotracers) and activity of the prefrontal cortex during working memory as measured with BOLD fMRI, which was positive in GG subjects and negative in GT. Our results demonstrate that this functional SNP within DRD2 predicts striatal binding of the two radiotracers to dopamine transporters and D2 receptors as well as the correlation between striatal D2 signaling with prefrontal cortex activity during performance of a working memory task. These data are consistent with the possibility that the balance of excitatory/inhibitory modulation of striatal neurons may also affect striatal outputs in relationship with prefrontal activity during working memory performance within the cortico-striatal-thalamic-cortical pathway.

  10. Genetically determined measures of striatal D2 signaling predict prefrontal activity during working memory performance.

    Directory of Open Access Journals (Sweden)

    Alessandro Bertolino

    2010-02-01

    Full Text Available Variation of the gene coding for D2 receptors (DRD2 has been associated with risk for schizophrenia and with working memory deficits. A functional intronic SNP (rs1076560 predicts relative expression of the two D2 receptors isoforms, D2S (mainly pre-synaptic and D2L (mainly post-synaptic. However, the effect of functional genetic variation of DRD2 on striatal dopamine D2 signaling and on its correlation with prefrontal activity during working memory in humans is not known.Thirty-seven healthy subjects were genotyped for rs1076560 (G>T and underwent SPECT with [123I]IBZM (which binds primarily to post-synaptic D2 receptors and with [123I]FP-CIT (which binds to pre-synaptic dopamine transporters, whose activity and density is also regulated by pre-synaptic D2 receptors, as well as BOLD fMRI during N-Back working memory.Subjects carrying the T allele (previously associated with reduced D2S expression had striatal reductions of [123I]IBZM and of [123I]FP-CIT binding. DRD2 genotype also differentially predicted the correlation between striatal dopamine D2 signaling (as identified with factor analysis of the two radiotracers and activity of the prefrontal cortex during working memory as measured with BOLD fMRI, which was positive in GG subjects and negative in GT.Our results demonstrate that this functional SNP within DRD2 predicts striatal binding of the two radiotracers to dopamine transporters and D2 receptors as well as the correlation between striatal D2 signaling with prefrontal cortex activity during performance of a working memory task. These data are consistent with the possibility that the balance of excitatory/inhibitory modulation of striatal neurons may also affect striatal outputs in relationship with prefrontal activity during working memory performance within the cortico-striatal-thalamic-cortical pathway.

  11. Predicting recurrent aphthous ulceration using genetic algorithms-optimized neural networks

    Directory of Open Access Journals (Sweden)

    Najla S Dar-Odeh

    2010-05-01

    Full Text Available Najla S Dar-Odeh1, Othman M Alsmadi2, Faris Bakri3, Zaer Abu-Hammour2, Asem A Shehabi3, Mahmoud K Al-Omiri1, Shatha M K Abu-Hammad4, Hamzeh Al-Mashni4, Mohammad B Saeed4, Wael Muqbil4, Osama A Abu-Hammad1 1Faculty of Dentistry, 2Faculty of Engineering and Technology, 3Faculty of Medicine, University of Jordan, Amman, Jordan; 4Dental Department, University of Jordan Hospital, Amman, JordanObjective: To construct and optimize a neural network that is capable of predicting the occurrence of recurrent aphthous ulceration (RAU based on a set of appropriate input data.Participants and methods: Artificial neural networks (ANN software employing genetic algorithms to optimize the architecture neural networks was used. Input and output data of 86 participants (predisposing factors and status of the participants with regards to recurrent aphthous ulceration were used to construct and train the neural networks. The optimized neural networks were then tested using untrained data of a further 10 participants.Results: The optimized neural network, which produced the most accurate predictions for the presence or absence of recurrent aphthous ulceration was found to employ: gender, hematological (with or without ferritin and mycological data of the participants, frequency of tooth brushing, and consumption of vegetables and fruits.Conclusions: Factors appearing to be related to recurrent aphthous ulceration and appropriate for use as input data to construct ANNs that predict recurrent aphthous ulceration were found to include the following: gender, hemoglobin, serum vitamin B12, serum ferritin, red cell folate, salivary candidal colony count, frequency of tooth brushing, and the number of fruits or vegetables consumed daily.Keywords: artifical neural networks, recurrent, aphthous ulceration, ulcer

  12. How does the predicted geomagnetic main field variation alter the thermosphere-ionosphere storm-time response?

    Science.gov (United States)

    Maute, A. I.; Lu, G.; Richmond, A. D.

    2017-12-01

    Earth's magnetic main field plays an important role in the thermosphere-ionosphere (TI) system, as well as its coupling to Earth's magnetosphere. The ionosphere consists of a weakly ionized plasma strongly influenced by the main field and embedded in the thermosphere. Therefore, ion-neutral coupling and ionospheric electrodynamics can influence the plasma distribution and neutral dynamics. There are strong longitude variations of the TI storm response. At high latitude magnetosphere-ionosphere coupling is organized by the geomagnetic main field, leading in general to stronger northern middle latitude storm time response in the American sector due to the geomagnetic dipole location. In addition, the weak geomagnetic main field in the American sector leads to larger local ExB drift and can alter the plasma densities. During geomagnetic storms the intense energy input into the high latitude region is redistributed globally, leading to thermospheric heating, wind circulation changes and alterations of the ionospheric electrodynamics. The storm time changes are measurable in the plasma density, ion drift, temperature, neutral composition, and other parameters. All these changes depend, to some degree, on the geomagnetic main field which changes on decadal time scales. In this study, we employ a forecast model of the geomagnetic main field based on data assimilation and geodynamo modeling [Aubert et al., 2015]. The main field model predicts that in 50 years the South Atlantic Anomaly is further weakened by 2 mT and drifts westward by approximately 10o. The dipole axis moves northward and westward by 2o and 6o, respectively. Simulating the March 2015 geomagnetic storm with the Thermosphere-Ionosphere Electrodynamics General Circulation Model (TIE-GCM) driven by the Assimilative Mapping of Ionospheric Electrodynamics (AMIE), we evaluate the thermosphere-ionosphere response using the geomagnetic main field of 2015, 2065, and 2115. We compare the TI response for 2015 with

  13. Prepubertal Ovariectomy Exaggerates Adult Affective Behaviors and Alters the Hippocampal Transcriptome in a Genetic Rat Model of Depression

    Directory of Open Access Journals (Sweden)

    Neha S. Raghavan

    2018-01-01

    Full Text Available Major depressive disorder (MDD is a debilitating illness that affects twice as many women than men postpuberty. This female bias is thought to be caused by greater heritability of MDD in women and increased vulnerability induced by female sex hormones. We tested this hypothesis by removing the ovaries from prepubertal Wistar Kyoto (WKY more immobile (WMI females, a genetic animal model of depression, and its genetically close control, the WKY less immobile (WLI. In adulthood, prepubertally ovariectomized (PrePubOVX animals and their Sham-operated controls were tested for depression- and anxiety-like behaviors, using the routinely employed forced swim and open field tests, respectively, and RNA-sequencing was performed on their hippocampal RNA. Our results confirmed that the behavioral and hippocampal expression changes that occur after prepubertal ovariectomy are the consequences of an interaction between genetic predisposition to depressive behavior and ovarian hormone-regulated processes. Lack of ovarian hormones during and after puberty in the WLIs led to increased depression-like behavior. In WMIs, both depression- and anxiety-like behaviors worsened by prepubertal ovariectomy. The unbiased exploration of the hippocampal transcriptome identified sets of differentially expressed genes (DEGs between the strains and treatment groups. The relatively small number of hippocampal DEGs resulting from the genetic differences between the strains confirmed the genetic relatedness of these strains. Nevertheless, the differences in DEGs between the strains in response to prepubertal ovariectomy identified different molecular processes, including the importance of glucocorticoid receptor-mediated mechanisms, that may be causative of the increased depression-like behavior in the presence or absence of genetic predisposition. This study contributes to the understanding of hormonal maturation-induced changes in affective behaviors and the hippocampal

  14. Genetic polymorphisms in 19q13.3 genes associated with alteration of repair capacity to BPDE-DNA adducts in primary cultured lymphocytes.

    Science.gov (United States)

    Xiao, Mingyang; Xiao, Sha; Straaten, Tahar van der; Xue, Ping; Zhang, Guopei; Zheng, Xiao; Zhang, Qianye; Cai, Yuan; Jin, Cuihong; Yang, Jinghua; Wu, Shengwen; Zhu, Guolian; Lu, Xiaobo

    2016-12-01

    Benzo[a]pyrene(B[a]P), and its ultimate metabolite Benzo[a]pyrene 7,8-diol 9,10-epoxide (BPDE), are classic DNA damaging carcinogens. DNA damage in cells caused by BPDE is normally repaired by Nucleotide Excision Repair (NER) and Base Excision Repair (BER). Genetic variations in NER and BER can change individual DNA repair capacity to DNA damage induced by BPDE. In the present study we determined the number of in vitro induced BPDE-DNA adducts in lymphocytes, to reflect individual susceptibility to Polycyclic aromatic hydrocarbons (PAHs)-induced carcinogenesis. The BPDE-DNA adduct level in lymphocytes were assessed by high performance liquid chromatography (HPLC) in 281 randomly selected participants. We genotyped for 9 single nucleotide polymorphisms (SNPs) in genes involved in NER (XPB rs4150441, XPC rs2228001, rs2279017 and XPF rs4781560), BER (XRCC1 rs25487, rs25489 and rs1799782) and genes located on chromosome 19q13.2-3 (PPP1R13L rs1005165 and CAST rs967591). We found that 3 polymorphisms in chromosome 19q13.2-3 were associated with lower levels of BPDE-DNA adducts (MinorT allele in XRCC1 rs1799782, minor T allele in PPP1R13L rs1005165 and minor A allele in CAST rs967571). In addition, a modified comet assay was performed to further confirm the above conclusions. We found both minor T allele in PPP1R13L rs1005165 and minor A allele in CAST rs967571 were associated with the lower levels of BPDE-adducts. Our data suggested that the variant genotypes of genes in chromosome 19q13.2-3 are associated with the alteration of repair efficiency to DNA damage caused by Benzo[a]pyrene, and may contribute to enhance predictive value for individual's DNA repair capacity in response to environmental carcinogens. Copyright © 2016 Elsevier B.V. All rights reserved.

  15. The Protective Effect of Minocycline in a Paraquat-Induced Parkinson's Disease Model in Drosophila is Modified in Altered Genetic Backgrounds

    Directory of Open Access Journals (Sweden)

    Arati A. Inamdar

    2012-01-01

    Full Text Available Epidemiological studies link the herbicide paraquat to increased incidence of Parkinson's disease (PD. We previously reported that Drosophila exposed to paraquat recapitulate PD symptoms, including region-specific degeneration of dopaminergic neurons. Minocycline, a tetracycline derivative, exerts ameliorative effects in neurodegenerative disease models, including Drosophila. We investigated whether our environmental toxin-based PD model could contribute to an understanding of cellular and genetic mechanisms of minocycline action and whether we could assess potential interference with these drug effects in altered genetic backgrounds. Cofeeding of minocycline with paraquat prolonged survival, rescued mobility defects, blocked generation of reactive oxygen species, and extended dopaminergic neuron survival, as has been reported previously for a genetic model of PD in Drosophila. We then extended this study to identify potential interactions of minocycline with genes regulating dopamine homeostasis that might modify protection against paraquat and found that deficits in GTP cyclohydrolase adversely affect minocycline rescue. We further performed genetic studies to identify signaling pathways that are necessary for minocycline protection against paraquat toxicity and found that mutations in the Drosophila genes that encode c-Jun N-terminal kinase (JNK and Akt/Protein kinase B block minocycline rescue.

  16. Addition of host genetic variants in a prediction rule for post meningitis hearing loss in childhood: a model updating study.

    Science.gov (United States)

    Sanders, Marieke S; de Jonge, Rogier C J; Terwee, Caroline B; Heymans, Martijn W; Koomen, Irene; Ouburg, Sander; Spanjaard, Lodewijk; Morré, Servaas A; van Furth, A Marceline

    2013-07-23

    Sensorineural hearing loss is the most common sequela in survivors of bacterial meningitis (BM). In the past we developed a validated prediction model to identify children at risk for post-meningitis hearing loss. It is known that host genetic variations, besides clinical factors, contribute to severity and outcome of BM. In this study it was determined whether host genetic risk factors improve the predictive abilities of an existing model regarding hearing loss after childhood BM. Four hundred and seventy-one Dutch Caucasian childhood BM were genotyped for 11 single nucleotide polymorphisms (SNPs) in seven different genes involved in pathogen recognition. Genetic data were added to the original clinical prediction model and performance of new models was compared to the original model by likelihood ratio tests and the area under the curve (AUC) of the receiver operating characteristic curves. Addition of TLR9-1237 SNPs and the combination of TLR2 + 2477 and TLR4 + 896 SNPs improved the clinical prediction model, but not significantly (increase of AUC's from 0.856 to 0.861 and from 0.856 to 0.875 (p = 0.570 and 0.335, respectively). Other SNPs analysed were not linked to hearing loss. Although addition of genetic risk factors did not significantly improve the clinical prediction model for post-meningitis hearing loss, AUC's of the pre-existing model remain high after addition of genetic factors. Future studies should evaluate whether more combinations of SNPs in larger cohorts has an additional value to the existing prediction model for post meningitis hearing loss.

  17. Simple, standardized incorporation of genetic risk into non-genetic risk prediction tools for complex traits: coronary heart disease as an example

    Directory of Open Access Journals (Sweden)

    Benjamin A Goldstein

    2014-08-01

    Full Text Available Purpose: Genetic risk assessment is becoming an important component of clinical decision-making. Genetic Risk Scores (GRSs allow the composite assessment of genetic risk in complex traits. A technically and clinically pertinent question is how to most easily and effectively combine a GRS with an assessment of clinical risk derived from established non-genetic risk factors as well as to clearly present this information to patient and health care providers. Materials & Methods: We illustrate a means to combine a GRS with an independent assessment of clinical risk using a log-link function. We apply the method to the prediction of coronary heart disease (CHD in the Atherosclerosis Risk in Communities (ARIC cohort. We evaluate different constructions based on metrics of effect change, discrimination, and calibration.Results: The addition of a GRS to a clinical risk score (CRS improves both discrimination and calibration for CHD in ARIC. Results are similar regardless of whether external vs. internal coefficients are used for the CRS, risk factor SNPs are included in the GRS, or subjects with diabetes at baseline are excluded. We outline how to report the construction and the performance of a GRS using our method and illustrate a means to present genetic risk information to subjects and/or their health care provider. Conclusion: The proposed method facilitates the standardized incorporation of a GRS in risk assessment.

  18. An acute rat in vivo screening model to predict compounds that alter blood glucose and/or insulin regulation.

    Science.gov (United States)

    Brott, David A; Diamond, Melody; Campbell, Pam; Zuvich, Andy; Cheatham, Letitia; Bentley, Patricia; Gorko, Mary Ann; Fikes, James; Saye, JoAnne

    2013-01-01

    Drug-induced glucose dysregulation and insulin resistance have been associated with weight gain and potential induction and/or exacerbation of diabetes mellitus in the clinic suggesting they may be safety biomarkers when developing antipsychotics. Glucose and insulin have also been suggested as potential efficacy biomarkers for some oncology compounds. The objective of this study was to qualify a medium throughput rat in vivo acute Intravenous Glucose Tolerance Test (IVGTT) for predicting compounds that will induce altered blood glucose and/or insulin levels. Acute and sub-chronic studies were performed to qualify an acute IVGTT model. Double cannulated male rats (Han-Wistar and Sprague-Dawley) were administered vehicle, olanzapine, aripiprazole or other compounds at t=-44min for acute studies and at time=-44min on the last day of dosing for sub-chronic studies, treated with dextrose (time=0min; i.v.) and blood collected using an automated Culex® system for glucose and insulin analysis (time=-45, -1, 2, 10, 15, 30, 45, 60, 75, 90, 120, 150 and 180min). Olanzapine significantly increased glucose and insulin area under the curve (AUC) values while aripiprazole AUC values were similar to control, in both acute and sub-chronic studies. All atypical antipsychotics evaluated were consistent with literature references of clinical weight gain. As efficacy biomarkers, insulin AUC but not glucose AUC values were increased with a compound known to have insulin growth factor-1 (IGF-1) activity, compared to control treatment. These studies qualified the medium throughput acute IVGTT model to more quickly screen compounds for 1) safety - the potential to elicit glucose dysregulation and/or insulin resistance and 2) efficacy - as a surrogate for compounds affecting the glucose and/or insulin regulatory pathways. These data demonstrate that the same in vivo rat model and assays can be used to predict both clinical safety and efficacy of compounds. © 2013.

  19. The RadGenomics project. Prediction for radio-susceptibility of individuals with genetic predisposition

    International Nuclear Information System (INIS)

    Imai, Takashi

    2003-01-01

    The ultimate goal of our project, named RadGenomics, is to elucidate the heterogeneity of the response to ionizing radiation arising from genetic variation among individuals, for the purpose of developing personalized radiation therapy regimens for cancer patients. Cancer patients exhibit patient-to-patient variability in normal tissue reactions after radiotherapy. Several observations support the hypothesis that the radiosensitivity of normal tissue is influenced by genetic factors. The rapid progression of human genome sequencing and the recent development of new technologies in molecular biology are providing new opportunities for elucidating the genetic basis of individual differences in susceptibility to radiation exposure. The development of a sufficiently robust, predictive assay enabling individual dose adjustment would improve the outcome of radiation therapy in patients. Our strategy for identification of DNA polymorphisms that contribute to the individual radiosensitivity is as follows. First, we have been categorizing DNA samples obtained from cancer patients, who have been kindly introduced to us through many collaborators, according to their clinical characteristics including the method and effect of treatment and side effects as scored by toxicity criteria, and also the result of an in vitro radiosensitivity assay, e.g., the micronuclei assay of their lymphocytes. Second, we have identified candidate genes for genotyping mainly by using our custom-designed oligonucleotide array with RNA samples, in which the probes were obtained from more than 40 cancer and 3 fibroblast cell lines whose radiosensitivity level was quite heterogeneous. We have also been studying the modification of proteins after irradiation of cells which may be caused by mainly phosphorylation or dephosphorylation, using mass spectrometry. Genes encoding the modified proteins and/or other proteins with which they interact such as specific protein kinases and phosphatases are also

  20. A genetic risk score combining ten psoriasis risk loci improves disease prediction.

    Directory of Open Access Journals (Sweden)

    Haoyan Chen

    2011-04-01

    Full Text Available Psoriasis is a chronic, immune-mediated skin disease affecting 2-3% of Caucasians. Recent genetic association studies have identified multiple psoriasis risk loci; however, most of these loci contribute only modestly to disease risk. In this study, we investigated whether a genetic risk score (GRS combining multiple loci could improve psoriasis prediction. Two approaches were used: a simple risk alleles count (cGRS and a weighted (wGRS approach. Ten psoriasis risk SNPs were genotyped in 2815 case-control samples and 858 family samples. We found that the total number of risk alleles in the cases was significantly higher than in controls, mean 13.16 (SD 1.7 versus 12.09 (SD 1.8, p = 4.577×10(-40. The wGRS captured considerably more risk than any SNP considered alone, with a psoriasis OR for high-low wGRS quartiles of 10.55 (95% CI 7.63-14.57, p = 2.010×10(-65. To compare the discriminatory ability of the GRS models, receiver operating characteristic curves were used to calculate the area under the curve (AUC. The AUC for wGRS was significantly greater than for cGRS (72.0% versus 66.5%, p = 2.13×10(-8. Additionally, the AUC for HLA-C alone (rs10484554 was equivalent to the AUC for all nine other risk loci combined (66.2% versus 63.8%, p = 0.18, highlighting the dominance of HLA-C as a risk locus. Logistic regression revealed that the wGRS was significantly associated with two subphenotypes of psoriasis, age of onset (p = 4.91×10(-6 and family history (p = 0.020. Using a liability threshold model, we estimated that the 10 risk loci account for only 11.6% of the genetic variance in psoriasis. In summary, we found that a GRS combining 10 psoriasis risk loci captured significantly more risk than any individual SNP and was associated with early onset of disease and a positive family history. Notably, only a small fraction of psoriasis heritability is captured by the common risk variants identified to date.

  1. FADS2 Genetic Variance in Combination with Fatty Acid Intake Might Alter Composition of the Fatty Acids in Brain.

    Directory of Open Access Journals (Sweden)

    Thais S Rizzi

    Full Text Available Multiple lines of evidence suggest that fatty acids (FA play an important role in cognitive function. However, little is known about the functional genetic pathways involved in cognition. The main goals of this study were to replicate previously reported interaction effects between breast feeding (BF and FA desaturase (FADS genetic variation on IQ and to investigate the possible mechanisms by which these variants might moderate BF effect, focusing on brain expression. Using a sample of 534 twins, we observed a trend in the moderation of BF effects on IQ by FADS2 variation. In addition, we made use of publicly available gene expression databases from both humans (193 and mice (93 and showed that FADS2 variants also correlate with FADS1 brain expression (P-value<1.1E-03. Our results provide novel clues for the understanding of the genetic mechanisms regulating FA brain expression and improve the current knowledge of the FADS moderation effect on cognition.

  2. Predicting the severity of nuclear power plant transients using nearest neighbors modeling optimized by genetic algorithms on a parallel computer

    International Nuclear Information System (INIS)

    Lin, J.; Bartal, Y.; Uhrig, R.E.

    1995-01-01

    The importance of automatic diagnostic systems for nuclear power plants (NPPs) has been discussed in numerous studies, and various such systems have been proposed. None of those systems were designed to predict the severity of the diagnosed scenario. A classification and severity prediction system for NPP transients is developed. The system is based on nearest neighbors modeling, which is optimized using genetic algorithms. The optimization process is used to determine the most important variables for each of the transient types analyzed. An enhanced version of the genetic algorithms is used in which a local downhill search is performed to further increase the accuracy achieved. The genetic algorithms search was implemented on a massively parallel supercomputer, the KSR1-64, to perform the analysis in a reasonable time. The data for this study were supplied by the high-fidelity simulator of the San Onofre unit 1 pressurized water reactor

  3. Understanding invasion history and predicting invasive niches using genetic sequencing technology in Australia: case studies from Cucurbitaceae and Boraginaceae.

    Science.gov (United States)

    Shaik, Razia S; Zhu, Xiaocheng; Clements, David R; Weston, Leslie A

    2016-01-01

    Part of the challenge in dealing with invasive plant species is that they seldom represent a uniform, static entity. Often, an accurate understanding of the history of plant introduction and knowledge of the real levels of genetic diversity present in species and populations of importance is lacking. Currently, the role of genetic diversity in promoting the successful establishment of invasive plants is not well defined. Genetic profiling of invasive plants should enhance our understanding of the dynamics of colonization in the invaded range. Recent advances in DNA sequencing technology have greatly facilitated the rapid and complete assessment of plant population genetics. Here, we apply our current understanding of the genetics and ecophysiology of plant invasions to recent work on Australian plant invaders from the Cucurbitaceae and Boraginaceae. The Cucurbitaceae study showed that both prickly paddy melon ( Cucumis myriocarpus ) and camel melon ( Citrullus lanatus ) were represented by only a single genotype in Australia, implying that each was probably introduced as a single introduction event. In contrast, a third invasive melon, Citrullus colocynthis , possessed a moderate level of genetic diversity in Australia and was potentially introduced to the continent at least twice. The Boraginaceae study demonstrated the value of comparing two similar congeneric species; one, Echium plantagineum , is highly invasive and genetically diverse, whereas the other, Echium vulgare , exhibits less genetic diversity and occupies a more limited ecological niche. Sequence analysis provided precise identification of invasive plant species, as well as information on genetic diversity and phylogeographic history. Improved sequencing technologies will continue to allow greater resolution of genetic relationships among invasive plant populations, thereby potentially improving our ability to predict the impact of these relationships upon future spread and better manage invaders

  4. Feasibility of an Assessment Tool for Children's Competence to Consent to Predictive Genetic Testing: a Pilot Study

    NARCIS (Netherlands)

    Hein, Irma M.; Troost, Pieter W.; Lindeboom, Robert; Christiaans, Imke; Grisso, Thomas; van Goudoever, Johannes B.; Lindauer, Ramón J. L.

    2015-01-01

    Knowledge on children's capacities to consent to medical treatment is limited. Also, age limits for asking children's consent vary considerably between countries. Decision-making on predictive genetic testing (PGT) is especially complicated, considering the ongoing ethical debate. In order to

  5. Addition of host genetic variants in a prediction rule for post meningitis hearing loss in childhood: a model updating study

    NARCIS (Netherlands)

    Sanders, Marieke S.; de Jonge, Rogier C. J.; Terwee, Caroline B.; Heymans, Martijn W.; Koomen, Irene; Ouburg, Sander; Spanjaard, Lodewijk; Morré, Servaas A.; van Furth, A. Marceline

    2013-01-01

    Sensorineural hearing loss is the most common sequela in survivors of bacterial meningitis (BM). In the past we developed a validated prediction model to identify children at risk for post-meningitis hearing loss. It is known that host genetic variations, besides clinical factors, contribute to

  6. The common sense model of self-regulation and psychological adjustment to predictive genetic testing: a prospective study

    NARCIS (Netherlands)

    van Oostrom, Iris; Meijers-Heijboer, Hanne; Duivenvoorden, Hugo J.; Bröcker-Vriends, Annette H. J. T.; van Asperen, Christi J.; Sijmons, Rolf H.; Seynaeve, Caroline; van Gool, Arthur R.; Klijn, Jan G. M.; Tibben, Aad

    2007-01-01

    This prospective study explored the contribution of illness representations and coping to cancer-related distress in unaffected individuals undergoing predictive genetic testing for an identified mutation in BRCA1/2 (BReast CAncer) or an HNPCC (Hereditary Nonpolyposis Colorectal Cancer)-related

  7. The common sense model of self-regulation and psychological adjustment to predictive genetic testing: a prospective study.

    NARCIS (Netherlands)

    Oostrom, I.I.H. van; Meijers-Heijboer, H.; Duivenvoorden, H.J.; Brocker-Vriends, A.H.; Asperen, C.J. van; Sijmons, R.H.; Seynaeve, C.; Gool, A.R. van; Klijn, J.G.M.; Tibben, A.

    2007-01-01

    This prospective study explored the contribution of illness representations and coping to cancer-related distress in unaffected individuals undergoing predictive genetic testing for an identified mutation in BRCA1/2 (BReast CAncer) or an HNPCC (Hereditary Nonpolyposis Colorectal Cancer)-related

  8. The common sense model of self-regulation and psychological adjustment to predictive genetic testing : a prospective study

    NARCIS (Netherlands)

    van Oostrom, Iris; Meijers-Heijboer, Hanne; Duivenvoorden, Hugo J.; Broecker-Vriends, Annette H. J. T.; van Asperen, Christi J.; Sijmons, Rolf H.; Seynaeve, Caroline; Van Gool, Arthur R.; Klijn, Jan G. M.; Tibben, Aad

    2007-01-01

    This prospective study explored the contribution of illness representations and coping to cancer-related distress in unaffected individuals undergoing predictive genetic testing for an identified mutation in BRCA1/2 (BReast CAncer) or an HNPCC (Hereditary Nonpolyposis Colorectal Cancer)-related

  9. Predicted global warming scenarios impact on the mother plant to alter seed dormancy and germination behaviour in Arabidopsis.

    Science.gov (United States)

    Huang, Z; Footitt, S; Tang, A; Finch-Savage, W E

    2018-01-01

    Seed characteristics are key components of plant fitness that are influenced by temperature in their maternal environment, and temperature will change with global warming. To study the effect of such temperature changes, Arabidopsis thaliana plants were grown to produce seeds along a uniquely designed polyethylene tunnel having a thermal gradient reflecting local global warming predictions. Plants therefore experienced the same variations in temperature and light conditions but different mean temperatures. A range of seed-related plant fitness estimates were measured. There were dramatic non-linear temperature effects on the germination behaviour in two contrasting ecotypes. Maternal temperatures lower than 15-16 °C resulted in significantly greater primary dormancy. In addition, the impact of nitrate in the growing media on dormancy was shown only by seeds produced below 15-16 °C. However, there were no consistent effects on seed yield, number, or size. Effects on germination behaviour were shown to be a species characteristic responding to temperature and not time of year. Elevating temperature above this critical value during seed development has the potential to dramatically alter the timing of subsequent seed germination and the proportion entering the soil seed bank. This has potential consequences for the whole plant life cycle and species fitness. © 2017 John Wiley & Sons Ltd.

  10. Hyperparameter Optimization of Artificial Neural Network in Customer Churn Prediction using Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Martin Fridrich

    2017-06-01

    Full Text Available Purpose of the article: The ability of the company to predict customer churn and retain customers is considered to be worthy competitive advantage since it improves cost allocation in customer retention programs, retaining future revenue and profits. In addition, it has several positive indirect impacts such as increasing customer’s loyalty. Therefore, the focus of the article is on building highly reliable and robust classification model, which deals with such a task. Methodology/methods: The analysis is carried out on labelled ecommerce retail dataset describing 10 000 most valuable customers with the highest CLV (Customer Lifetime Value. To obtain the best performing ANN (Artificial Neural Network classification model, proposed hyperparameter search space is explored with genetic algorithm to find suitable parameter settings. ANN classification performance is measured with regard to prediction ability, which is understood as point estimate of AUC (Area Under Curve mean on 4fold cross-validation set. Explored part of hyperparameter search space is analyzed with conditional inference tree structure addressing underlying fundamental context of given optimization which results in identification of critical factors leading to well performing ANN classification model. Scientific aim: To present and execute experimental design for performance evaluation and hyperparameter optimization of classification models, which are used for customer churn prediction. Findings: It is concluded and statistically proven that in experimental context described, regularization parameter as well as training function have significant influence on classifiers AUC performance contrasting other properties of ANN. More specifically, well performing ANN classification models have regularization parameter set to 0, adaptation function set to trainlm or trainscg and more than 100 training epochs. Global optimum is identified for solution with regularization parameter set to

  11. Genetic and epigenetic alterations of the reduced folate carrier in untreated diffuse large B-cell lymphoma

    DEFF Research Database (Denmark)

    Kastrup, Ingelise Bjerring; Worm, Jesper; Ralfkiaer, Elisabeth

    2007-01-01

    The reduced folate carrier (RFC) is a transmembrane protein that mediates cellular uptake of reduced folates and antifolate drugs, including methotrexate (MTX). Acquired alterations of the RFC gene have been associated with resistance to MTX in cancer cell lines and primary osteosarcomas. Here, we...

  12. Genetics

    DEFF Research Database (Denmark)

    Christensen, Kaare; McGue, Matt

    2016-01-01

    The sequenced genomes of individuals aged ≥80 years, who were highly educated, self-referred volunteers and with no self-reported chronic diseases were compared to young controls. In these data, healthy ageing is a distinct phenotype from exceptional longevity and genetic factors that protect...

  13. Predicting cell types and genetic variations contributing to disease by combining GWAS and epigenetic data.

    Directory of Open Access Journals (Sweden)

    Anna Gerasimova

    Full Text Available Genome-wide association studies (GWASs identify single nucleotide polymorphisms (SNPs that are enriched in individuals suffering from a given disease. Most disease-associated SNPs fall into non-coding regions, so that it is not straightforward to infer phenotype or function; moreover, many SNPs are in tight genetic linkage, so that a SNP identified as associated with a particular disease may not itself be causal, but rather signify the presence of a linked SNP that is functionally relevant to disease pathogenesis. Here, we present an analysis method that takes advantage of the recent rapid accumulation of epigenomics data to address these problems for some SNPs. Using asthma as a prototypic example; we show that non-coding disease-associated SNPs are enriched in genomic regions that function as regulators of transcription, such as enhancers and promoters. Identifying enhancers based on the presence of the histone modification marks such as H3K4me1 in different cell types, we show that the location of enhancers is highly cell-type specific. We use these findings to predict which SNPs are likely to be directly contributing to disease based on their presence in regulatory regions, and in which cell types their effect is expected to be detectable. Moreover, we can also predict which cell types contribute to a disease based on overlap of the disease-associated SNPs with the locations of enhancers present in a given cell type. Finally, we suggest that it will be possible to re-analyze GWAS studies with much higher power by limiting the SNPs considered to those in coding or regulatory regions of cell types relevant to a given disease.

  14. Single-Event Transgene Product Levels Predict Levels in Genetically Modified Breeding Stacks.

    Science.gov (United States)

    Gampala, Satyalinga Srinivas; Fast, Brandon J; Richey, Kimberly A; Gao, Zhifang; Hill, Ryan; Wulfkuhle, Bryant; Shan, Guomin; Bradfisch, Greg A; Herman, Rod A

    2017-09-13

    The concentration of transgene products (proteins and double-stranded RNA) in genetically modified (GM) crop tissues is measured to support food, feed, and environmental risk assessments. Measurement of transgene product concentrations in breeding stacks of previously assessed and approved GM events is required by many regulatory authorities to evaluate unexpected transgene interactions that might affect expression. Research was conducted to determine how well concentrations of transgene products in single GM events predict levels in breeding stacks composed of these events. The concentrations of transgene products were compared between GM maize, soybean, and cotton breeding stacks (MON-87427 × MON-89034 × DAS-Ø15Ø7-1 × MON-87411 × DAS-59122-7 × DAS-40278-9 corn, DAS-81419-2 × DAS-44406-6 soybean, and DAS-21023-5 × DAS-24236-5 × SYN-IR102-7 × MON-88913-8 × DAS-81910-7 cotton) and their component single events (MON-87427, MON-89034, DAS-Ø15Ø7-1, MON-87411, DAS-59122-7, and DAS-40278-9 corn, DAS-81419-2, and DAS-44406-6 soybean, and DAS-21023-5, DAS-24236-5, SYN-IR102-7, MON-88913-8, and DAS-81910-7 cotton). Comparisons were made within a crop and transgene product across plant tissue types and were also made across transgene products in each breeding stack for grain/seed. Scatter plots were generated comparing expression in the stacks to their component events, and the percent of variability accounted for by the line of identity (y = x) was calculated (coefficient of identity, I 2 ). Results support transgene concentrations in single events predicting similar concentrations in breeding stacks containing the single events. Therefore, food, feed, and environmental risk assessments based on concentrations of transgene products in single GM events are generally applicable to breeding stacks composed of these events.

  15. Alteration of sexual reproduction and genetic diversity in the kelp species Laminaria digitata at the southern limit of its range.

    Directory of Open Access Journals (Sweden)

    Luz Valeria Oppliger

    Full Text Available Adaptation to marginal habitats at species range-limits has often been associated with parthenogenetic reproduction in terrestrial animals and plants. Laboratory observations have shown that brown algae exhibit a high propensity for parthenogenesis by various mechanisms. The kelp Laminaria digitata is an important component of the ecosystem in Northern European rocky intertidal habitats. We studied four L. digitata populations for the effects of marginality on genetic diversity and sexual reproduction. Two populations were marginal: One (Locquirec, in Northern Brittany was well within the geographic range, but was genetically isolated from other populations by large stretches of sandy beaches. Another population was at the range limits of the species (Quiberon, in Southern Brittany and was exposed to much higher seasonal temperature changes. Microsatellite analyses confirmed that these populations showed decreased genetic and allelic diversity, consistent with marginality and genetic isolation. Sporophytes from both marginal populations showed greatly diminished spore-production compared to central populations, but only the southern-limit population (Quiberon showed a high propensity for producing unreduced (2N spores. Unreduced 2N spores formed phenotypically normal gametophytes with nuclear area consistent with ≥2N DNA contents, and microsatellite studies suggested these were produced at least in part by automixis. However, despite this being the dominant path of spore production in Quiberon sporophyte individuals, the genetic evidence indicated the population was maintained mostly by sexual reproduction. Thus, although spore production and development showed the expected tendency of geographical parthenogenesis in marginal populations, this appeared to be a consequence of maladaptation, rather than an adaptation to, life in a marginal habitat.

  16. Alterations in the α2 δ ligand, thrombospondin-1, in a rat model of spontaneous absence epilepsy and in patients with idiopathic/genetic generalized epilepsies.

    Science.gov (United States)

    Santolini, Ines; Celli, Roberta; Cannella, Milena; Imbriglio, Tiziana; Guiducci, Michela; Parisi, Pasquale; Schubert, Julian; Iacomino, Michele; Zara, Federico; Lerche, Holger; Moyanova, Slavianka; Ngomba, Richard Teke; van Luijtelaar, Gilles; Battaglia, Giuseppe; Bruno, Valeria; Striano, Pasquale; Nicoletti, Ferdinando

    2017-11-01

    Thrombospondins, which are known to interact with the α 2 δ subunit of voltage-sensitive calcium channels to stimulate the formation of excitatory synapses, have recently been implicated in the process of epileptogenesis. No studies have been so far performed on thrombospondins in models of absence epilepsy. We examined whether expression of the gene encoding for thrombospondin-1 was altered in the brain of WAG/Rij rats, which model absence epilepsy in humans. In addition, we examined the frequency of genetic variants of THBS1 in a large cohort of children affected by idiopathic/genetic generalized epilepsies (IGE/GGEs). We measured the transcripts of thrombospondin-1 and α 2 δ subunit, and protein levels of α 2 δ, Rab3A, and the vesicular glutamate transporter, VGLUT1, in the somatosensory cortex and ventrobasal thalamus of presymptomatic and symptomatic WAG/Rij rats and in two control strains by real-time polymerase chain reaction (PCR) and immunoblotting. We examined the genetic variants of THBS1 and CACNA2D1 in two independent cohorts of patients affected by IGE/GGE recruited through the Genetic Commission of the Italian League Against Epilepsy (LICE) and the EuroEPINOMICS-CoGIE Consortium. Thrombospondin-1 messenger RNA (mRNA) levels were largely reduced in the ventrobasal thalamus of both presymptomatic and symptomatic WAG/Rij rats, whereas levels in the somatosensory cortex were unchanged. VGLUT1 protein levels were also reduced in the ventrobasal thalamus of WAG/Rij rats. Genetic variants of THBS1 were significantly more frequent in patients affected by IGE/GGE than in nonepileptic controls, whereas the frequency of CACNA2D1 was unchanged. These findings suggest that thrombospondin-1 may have a role in the pathogenesis of IGE/GGEs. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

  17. Mixing Energy Models in Genetic Algorithms for On-Lattice Protein Structure Prediction

    Directory of Open Access Journals (Sweden)

    Mahmood A. Rashid

    2013-01-01

    Full Text Available Protein structure prediction (PSP is computationally a very challenging problem. The challenge largely comes from the fact that the energy function that needs to be minimised in order to obtain the native structure of a given protein is not clearly known. A high resolution 20×20 energy model could better capture the behaviour of the actual energy function than a low resolution energy model such as hydrophobic polar. However, the fine grained details of the high resolution interaction energy matrix are often not very informative for guiding the search. In contrast, a low resolution energy model could effectively bias the search towards certain promising directions. In this paper, we develop a genetic algorithm that mainly uses a high resolution energy model for protein structure evaluation but uses a low resolution HP energy model in focussing the search towards exploring structures that have hydrophobic cores. We experimentally show that this mixing of energy models leads to significant lower energy structures compared to the state-of-the-art results.

  18. Prediction of genetic gain from selection indices for disease resistance in papaya hybrids

    Directory of Open Access Journals (Sweden)

    Marcelo Vivas

    2012-12-01

    Full Text Available In order to select superior hybrids for the concentration of favorable alleles for resistance to papaya black spot, powdery mildew and phoma spot, 67 hybrids were evaluated in two seasons, in 2007, in a randomized block design with two replications. Genetic gains were estimated from the selection indices of Smith & Hazel, Pesek & Baker, Williams, Mulamba & Mock, with selection intensity of 22.39%, corresponding to 15 hybrids. The index of Mulamba & Mock showed gains more suitable for the five traits assessed when it was used the criterion of economic weight tentatively assigned. Together, severity of black spot on leaves and on fruits, characteristics considered most relevant to the selection of resistant materials, expressed percentage gain of -44.15%. In addition, there were gains for other characteristics, with negative predicted selective percentage gain. The results showed that the index of Mulamba & Mock is the most efficient procedure for simultaneous selection of papaya hybrid resistant to black spot, powdery mildew and phoma spot.

  19. BP neural network optimized by genetic algorithm approach for titanium and iron content prediction in EDXRF

    International Nuclear Information System (INIS)

    Wang Jun; Liu Mingzhe; Li Zhe; Li Lei; Shi Rui; Tuo Xianguo

    2015-01-01

    The quantitative elemental content analysis is difficult due to the uniform effect, particle effect and the element matrix effect, etc, when using energy dispersive X-ray fluorescence (EDXRF) technique. In this paper, a hybrid approach of genetic algorithm (GA) and back propagation (BP) neural network was proposed without considering the complex relationship between the concentration and intensity. The aim of GA optimized BP was to get better network initial weights and thresholds. The basic idea was that the reciprocal of the mean square error of the initialization BP neural network was set as the fitness value of the individual in GA, and the initial weights and thresholds were replaced by individuals, and then the optimal individual was sought by selection, crossover and mutation operations, finally a new BP neural network model was created with the optimal initial weights and thresholds. The calculation results of quantitative analysis of titanium and iron contents for five types of ore bodies in Panzhihua Mine show that the results of classification prediction are far better than that of overall forecasting, and relative errors of 76.7% samples are less than 2% compared with chemical analysis values, which demonstrates the effectiveness of the proposed method. (authors)

  20. Genetic Algorithms for Estimating Effective Parameters in a Lumped Reactor Model for Reactivity Predictions

    International Nuclear Information System (INIS)

    Marseguerra, Marzio; Zio, Enrico

    2001-01-01

    The control system of a reactor should be able to predict, in real time, the amount of reactivity to be inserted (e.g., by control rod movements and boron injection and dilution) to respond to a given electrical load demand or to undesired, accidental transients. The real-time constraint renders impractical the use of a large, detailed dynamic reactor code. One has, then, to resort to simplified analytical models with lumped effective parameters suitably estimated from the reactor data.The simple and well-known Chernick model for describing the reactor power evolution in the presence of xenon is considered and the feasibility of using genetic algorithms for estimating the effective nuclear parameters involved and the initial nonmeasurable xenon and iodine conditions is investigated. This approach has the advantage of counterbalancing the inherent model simplicity with the periodic reestimation of the effective parameter values pertaining to each reactor on the basis of its recent history. By so doing, other effects, such as burnup, are automatically taken into account

  1. Predicting temperature drop rate of mass concrete during an initial cooling period using genetic programming

    Science.gov (United States)

    Bhattarai, Santosh; Zhou, Yihong; Zhao, Chunju; Zhou, Huawei

    2018-02-01

    Thermal cracking on concrete dams depends upon the rate at which the concrete is cooled (temperature drop rate per day) within an initial cooling period during the construction phase. Thus, in order to control the thermal cracking of such structure, temperature development due to heat of hydration of cement should be dropped at suitable rate. In this study, an attempt have been made to formulate the relation between cooling rate of mass concrete with passage of time (age of concrete) and water cooling parameters: flow rate and inlet temperature of cooling water. Data measured at summer season (April-August from 2009 to 2012) from recently constructed high concrete dam were used to derive a prediction model with the help of Genetic Programming (GP) software “Eureqa”. Coefficient of Determination (R) and Mean Square Error (MSE) were used to evaluate the performance of the model. The value of R and MSE is 0.8855 and 0.002961 respectively. Sensitivity analysis was performed to evaluate the relative impact on the target parameter due to input parameters. Further, testing the proposed model with an independent dataset those not included during analysis, results obtained from the proposed GP model are close enough to the real field data.

  2. Predicting complex traits using a diffusion kernel on genetic markers with an application to dairy cattle and wheat data

    Science.gov (United States)

    2013-01-01

    Background Arguably, genotypes and phenotypes may be linked in functional forms that are not well addressed by the linear additive models that are standard in quantitative genetics. Therefore, developing statistical learning models for predicting phenotypic values from all available molecular information that are capable of capturing complex genetic network architectures is of great importance. Bayesian kernel ridge regression is a non-parametric prediction model proposed for this purpose. Its essence is to create a spatial distance-based relationship matrix called a kernel. Although the set of all single nucleotide polymorphism genotype configurations on which a model is built is finite, past research has mainly used a Gaussian kernel. Results We sought to investigate the performance of a diffusion kernel, which was specifically developed to model discrete marker inputs, using Holstein cattle and wheat data. This kernel can be viewed as a discretization of the Gaussian kernel. The predictive ability of the diffusion kernel was similar to that of non-spatial distance-based additive genomic relationship kernels in the Holstein data, but outperformed the latter in the wheat data. However, the difference in performance between the diffusion and Gaussian kernels was negligible. Conclusions It is concluded that the ability of a diffusion kernel to capture the total genetic variance is not better than that of a Gaussian kernel, at least for these data. Although the diffusion kernel as a choice of basis function may have potential for use in whole-genome prediction, our results imply that embedding genetic markers into a non-Euclidean metric space has very small impact on prediction. Our results suggest that use of the black box Gaussian kernel is justified, given its connection to the diffusion kernel and its similar predictive performance. PMID:23763755

  3. Genetic parameters for the prediction of abdominal fat traits using blood biochemical indicators in broilers.

    Science.gov (United States)

    Zhang, H L; Xu, Z Q; Yang, L L; Wang, Y X; Li, Y M; Dong, J Q; Zhang, X Y; Jiang, X Y; Jiang, X F; Li, H; Zhang, D X; Zhang, H

    2018-02-01

    1. Excessive deposition of body fat, especially abdominal fat, is detrimental in chickens and the prevention of excessive fat accumulation is an important problem. The aim of this study was to identify blood biochemical indicators that could be used as criteria to select lean Yellow-feathered chicken lines. 2. Levels of blood biochemical indicators in the fed and fasted states and the abdominal fat traits were measured in 332 Guangxi Yellow chickens. In the fed state, the genetic correlations (r g ) of triglycerides and very low density lipoprotein levels were positive for the abdominal fat traits (0.47 ≤ r g  ≤ 0.67), whereas total cholesterol, high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) showed higher negative correlations with abdominal fat traits (-0.59 ≤ r g  ≤ -0.33). Heritabilities of these blood biochemical parameters were high, varying from 0.26 to 0.60. 3. In the fasted state, HDL-C:LDL-C level was positively correlated with abdominal fat traits (0.35 ≤ r g  ≤ 0.38), but triglycerides, total cholesterol, HDL-C, LDL-C, total protein, albumin, aspartate transaminase, uric acid and creatinine levels were negatively correlated with abdominal fat traits (-0.79 ≤ r g  ≤ -0.35). The heritabilities of these 10 blood biochemical parameters were high (0.22 ≤ h 2  ≤ 0.59). 4. In the fed state, optimal multiple regression models were constructed to predict abdominal fat traits by using triglycerides and LDL-C. In the fasted state, triglycerides, total cholesterol, HDL-C, LDL-C, total protein, albumin and uric acid could be used to predict abdominal fat content. 5. It was concluded that these models in both nutritional states could be used to predict abdominal fat content in Guangxi Yellow broiler chickens.

  4. Touch imprint cytology with massively parallel sequencing (TIC-seq): a simple and rapid method to snapshot genetic alterations in tumors.

    Science.gov (United States)

    Amemiya, Kenji; Hirotsu, Yosuke; Goto, Taichiro; Nakagomi, Hiroshi; Mochizuki, Hitoshi; Oyama, Toshio; Omata, Masao

    2016-12-01

    Identifying genetic alterations in tumors is critical for molecular targeting of therapy. In the clinical setting, formalin-fixed paraffin-embedded (FFPE) tissue is usually employed for genetic analysis. However, DNA extracted from FFPE tissue is often not suitable for analysis because of its low levels and poor quality. Additionally, FFPE sample preparation is time-consuming. To provide early treatment for cancer patients, a more rapid and robust method is required for precision medicine. We present a simple method for genetic analysis, called touch imprint cytology combined with massively paralleled sequencing (touch imprint cytology [TIC]-seq), to detect somatic mutations in tumors. We prepared FFPE tissues and TIC specimens from tumors in nine lung cancer patients and one patient with breast cancer. We found that the quality and quantity of TIC DNA was higher than that of FFPE DNA, which requires microdissection to enrich DNA from target tissues. Targeted sequencing using a next-generation sequencer obtained sufficient sequence data using TIC DNA. Most (92%) somatic mutations in lung primary tumors were found to be consistent between TIC and FFPE DNA. We also applied TIC DNA to primary and metastatic tumor tissues to analyze tumor heterogeneity in a breast cancer patient, and showed that common and distinct mutations among primary and metastatic sites could be classified into two distinct histological subtypes. TIC-seq is an alternative and feasible method to analyze genomic alterations in tumors by simply touching the cut surface of specimens to slides. © 2016 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

  5. Prognostic and predictive values of EGFR overexpression and EGFR copy number alteration in HER2-positive breast cancer.

    Science.gov (United States)

    Lee, H J; Seo, A N; Kim, E J; Jang, M H; Kim, Y J; Kim, J H; Kim, S-W; Ryu, H S; Park, I A; Im, S-A; Gong, G; Jung, K H; Kim, H J; Park, S Y

    2015-01-06

    Epidermal growth factor receptor (EGFR) is overexpressed in a subset of human epidermal growth factor receptor 2 (HER2)-positive breast cancers, and coexpression of HER2 and EGFR has been reported to be associated with poor clinical outcome. Moreover, interaction between HER2 and EGFR has been suggested to be a possible basis for trastuzumab resistance. We analysed the clinical significance of EGFR overexpression and EGFR gene copy number alterations in 242 HER2-positive primary breast cancers. In addition, we examined the correlations between EGFR overexpression, trastuzumab response and clinical outcome in 447 primary, and 112 metastatic HER2-positive breast cancer patients treated by trastuzumab. Of the 242 primary cases, the level of EGFR overexpression was 2+ in 12.7% and 3+ in 11.8%. High EGFR gene copy number was detected in 10.3%. Epidermal growth factor receptor overexpression was associated with hormone receptor negativity and high Ki-67 proliferation index. In survival analyses, EGFR overexpression, but not high EGFR copy number, was associated with poor disease-free survival in all patients, and in the subgroup not receiving adjuvant trastuzumab. In 447 HER2-positive primary breast cancer patients treated with adjuvant trastuzumab, EGFR overexpression was also an independent poor prognostic factor. However, EGFR overexpression was not associated with trastuzumab response, progression-free survival or overall survival in the metastatic setting. Epidermal growth factor receptor overexpression, but not high EGFR copy number, is a poor prognostic factor in HER2-positive primary breast cancer. Epidermal growth factor receptor overexpression is a predictive factor for trastuzumab response in HER2-positive primary breast cancer, but not in metastatic breast cancer.

  6. Ethanol Exposure History and Alcoholic Reward Differentially Alter Dopamine Release in the Nucleus Accumbens to a Reward-Predictive Cue.

    Science.gov (United States)

    Fiorenza, Amanda M; Shnitko, Tatiana A; Sullivan, Kaitlin M; Vemuru, Sudheer R; Gomez-A, Alexander; Esaki, Julie Y; Boettiger, Charlotte A; Da Cunha, Claudio; Robinson, Donita L

    2018-06-01

    Conditioned stimuli (CS) that predict reward delivery acquire the ability to induce phasic dopamine release in the nucleus accumbens (NAc). This dopamine release may facilitate conditioned approach behavior, which often manifests as approach to the site of reward delivery (called "goal-tracking") or to the CS itself (called "sign-tracking"). Previous research has linked sign-tracking in particular to impulsivity and drug self-administration, and addictive drugs may promote the expression of sign-tracking. Ethanol (EtOH) acutely promotes phasic release of dopamine in the accumbens, but it is unknown whether an alcoholic reward alters dopamine release to a CS. We hypothesized that Pavlovian conditioning with an alcoholic reward would increase dopamine release triggered by the CS and subsequent sign-tracking behavior. Moreover, we predicted that chronic intermittent EtOH (CIE) exposure would promote sign-tracking while acute administration of naltrexone (NTX) would reduce it. Rats received 14 doses of EtOH (3 to 5 g/kg, intragastric) or water followed by 6 days of Pavlovian conditioning training. Rewards were a chocolate solution with or without 10% (w/v) alcohol. We used fast-scan cyclic voltammetry to measure phasic dopamine release in the NAc core in response to the CS and the rewards. We also determined the effect of NTX (1 mg/kg, subcutaneous) on conditioned approach. Both CIE and alcoholic reward, individually but not together, associated with greater dopamine to the CS than control conditions. However, this increase in dopamine release was not linked to greater sign-tracking, as both CIE and alcoholic reward shifted conditioned approach from sign-tracking behavior to goal-tracking behavior. However, they both also increased sensitivity to NTX, which reduced goal-tracking behavior. While a history of EtOH exposure or alcoholic reward enhanced dopamine release to a CS, they did not promote sign-tracking under the current conditions. These findings are

  7. Genetic relationships between carcass cut weights predicted from video image analysis and other performance traits in cattle.

    Science.gov (United States)

    Pabiou, T; Fikse, W F; Amer, P R; Cromie, A R; Näsholm, A; Berry, D P

    2012-09-01

    The objective of this study was to quantify the genetic associations between a range of carcass-related traits including wholesale cut weights predicted from video image analysis (VIA) technology, and a range of pre-slaughter performance traits in commercial Irish cattle. Predicted carcass cut weights comprised of cut weights based on retail value: lower value cuts (LVC), medium value cuts (MVC), high value cuts (HVC) and very high value cuts (VHVC), as well as total meat, fat and bone weights. Four main sources of data were used in the genetic analyses: price data of live animals collected from livestock auctions, live-weight data and linear type collected from both commercial and pedigree farms as well as from livestock auctions and weanling quality recorded on-farm. Heritability of carcass cut weights ranged from 0.21 to 0.39. Genetic correlations between the cut traits and the other performance traits were estimated using a series of bivariate sire linear mixed models where carcass cut weights were phenotypically adjusted to a constant carcass weight. Strongest positive genetic correlations were obtained between predicted carcass cut weights and carcass value (min r g(MVC) = 0.35; max r(g(VHVC)) = 0.69), and animal price at both weaning (min r(g(MVC)) = 0.37; max r(g(VHVC)) = 0.66) and post weaning (min r(g(MVC)) = 0.50; max r(g(VHVC)) = 0.67). Moderate genetic correlations were obtained between carcass cut weights and calf price (min r g(HVC) = 0.34; max r g(LVC) = 0.45), weanling quality (min r(g(MVC)) = 0.12; max r (g(VHVC)) = 0.49), linear scores for muscularity at both weaning (hindquarter development: min r(g(MVC)) = -0.06; max r(g(VHVC)) = 0.46), post weaning (hindquarter development: min r(g(MVC)) = 0.23; max r(g(VHVC)) = 0.44). The genetic correlations between total meat weight were consistent with those observed with the predicted wholesale cut weights. Total fat and total bone weights were generally negatively correlated with carcass value, auction

  8. The ties that bind: genetic relatedness predicts the fission and fusion of social groups in wild African elephants.

    Science.gov (United States)

    Archie, Elizabeth A; Moss, Cynthia J; Alberts, Susan C

    2006-03-07

    Many social animals live in stable groups. In contrast, African savannah elephants (Loxodonta africana) live in unusually fluid, fission-fusion societies. That is, 'core' social groups are composed of predictable sets of individuals; however, over the course of hours or days, these groups may temporarily divide and reunite, or they may fuse with other social groups to form much larger social units. Here, we test the hypothesis that genetic relatedness predicts patterns of group fission and fusion among wild, female African elephants. Our study of a single Kenyan population spans 236 individuals in 45 core social groups, genotyped at 11 microsatellite and one mitochondrial DNA (mtDNA) locus. We found that genetic relatedness predicted group fission; adult females remained with their first order maternal relatives when core groups fissioned temporarily. Relatedness also predicted temporary fusion between social groups; core groups were more likely to fuse with each other when the oldest females in each group were genetic relatives. Groups that shared mtDNA haplotypes were also significantly more likely to fuse than groups that did not share mtDNA. Our results suggest that associations between core social groups persist for decades after the original maternal kin have died. We discuss these results in the context of kin selection and its possible role in the evolution of elephant sociality.

  9. Prediction of Adulthood Obesity Using Genetic and Childhood Clinical Risk Factors in the Cardiovascular Risk in Young Finns Study.

    Science.gov (United States)

    Seyednasrollah, Fatemeh; Mäkelä, Johanna; Pitkänen, Niina; Juonala, Markus; Hutri-Kähönen, Nina; Lehtimäki, Terho; Viikari, Jorma; Kelly, Tanika; Li, Changwei; Bazzano, Lydia; Elo, Laura L; Raitakari, Olli T

    2017-06-01

    Obesity is a known risk factor for cardiovascular disease. Early prediction of obesity is essential for prevention. The aim of this study is to assess the use of childhood clinical factors and the genetic risk factors in predicting adulthood obesity using machine learning methods. A total of 2262 participants from the Cardiovascular Risk in YFS (Young Finns Study) were followed up from childhood (age 3-18 years) to adulthood for 31 years. The data were divided into training (n=1625) and validation (n=637) set. The effect of known genetic risk factors (97 single-nucleotide polymorphisms) was investigated as a weighted genetic risk score of all 97 single-nucleotide polymorphisms (WGRS97) or a subset of 19 most significant single-nucleotide polymorphisms (WGRS19) using boosting machine learning technique. WGRS97 and WGRS19 were validated using external data (n=369) from BHS (Bogalusa Heart Study). WGRS19 improved the accuracy of predicting adulthood obesity in training (area under the curve [AUC=0.787 versus AUC=0.744, P obesity. Predictive accuracy is highest among young children (3-6 years), whereas among older children (9-18 years) the risk can be identified using childhood clinical factors. The model is helpful in screening children with high risk of developing obesity. © 2017 American Heart Association, Inc.

  10. GRECOS Project (Genotyping Recurrence Risk of Stroke): The Use of Genetics to Predict the Vascular Recurrence After Stroke.

    Science.gov (United States)

    Fernández-Cadenas, Israel; Mendióroz, Maite; Giralt, Dolors; Nafria, Cristina; Garcia, Elena; Carrera, Caty; Gallego-Fabrega, Cristina; Domingues-Montanari, Sophie; Delgado, Pilar; Ribó, Marc; Castellanos, Mar; Martínez, Sergi; Freijo, Marimar; Jiménez-Conde, Jordi; Rubiera, Marta; Alvarez-Sabín, José; Molina, Carlos A; Font, Maria Angels; Grau Olivares, Marta; Palomeras, Ernest; Perez de la Ossa, Natalia; Martinez-Zabaleta, Maite; Masjuan, Jaime; Moniche, Francisco; Canovas, David; Piñana, Carlos; Purroy, Francisco; Cocho, Dolores; Navas, Inma; Tejero, Carlos; Aymerich, Nuria; Cullell, Natalia; Muiño, Elena; Serena, Joaquín; Rubio, Francisco; Davalos, Antoni; Roquer, Jaume; Arenillas, Juan Francisco; Martí-Fábregas, Joan; Keene, Keith; Chen, Wei-Min; Worrall, Bradford; Sale, Michele; Arboix, Adrià; Krupinski, Jerzy; Montaner, Joan

    2017-05-01

    Vascular recurrence occurs in 11% of patients during the first year after ischemic stroke (IS) or transient ischemic attack. Clinical scores do not predict the whole vascular recurrence risk; therefore, we aimed to find genetic variants associated with recurrence that might improve the clinical predictive models in IS. We analyzed 256 polymorphisms from 115 candidate genes in 3 patient cohorts comprising 4482 IS or transient ischemic attack patients. The discovery cohort was prospectively recruited and included 1494 patients, 6.2% of them developed a new IS during the first year of follow-up. Replication analysis was performed in 2988 patients using SNPlex or HumanOmni1-Quad technology. We generated a predictive model using Cox regression (GRECOS score [Genotyping Reurrence Risk of Stroke]) and generated risk groups using a classification tree method. The analyses revealed that rs1800801 in the MGP gene (hazard ratio, 1.33; P =9×10 - 03 ), a gene related to artery calcification, was associated with new IS during the first year of follow-up. This polymorphism was replicated in a Spanish cohort (n=1.305); however, it was not significantly associated in a North American cohort (n=1.683). The GRECOS score predicted new IS ( P =3.2×10 - 09 ) and could classify patients, from low risk of stroke recurrence (1.9%) to high risk (12.6%). Moreover, the addition of genetic risk factors to the GRECOS score improves the prediction compared with previous Stroke Prognosis Instrument-II score ( P =0.03). The use of genetics could be useful to estimate vascular recurrence risk after IS. Genetic variability in the MGP gene was associated with vascular recurrence in the Spanish population. © 2017 American Heart Association, Inc.

  11. Genetic Differences in the Immediate Transcriptome Response to Stress Predict Risk-Related Brain Function and Psychiatric Disorders

    Science.gov (United States)

    Arloth, Janine; Bogdan, Ryan; Weber, Peter; Frishman, Goar; Menke, Andreas; Wagner, Klaus V.; Balsevich, Georgia; Schmidt, Mathias V.; Karbalai, Nazanin; Czamara, Darina; Altmann, Andre; Trümbach, Dietrich; Wurst, Wolfgang; Mehta, Divya; Uhr, Manfred; Klengel, Torsten; Erhardt, Angelika; Carey, Caitlin E.; Conley, Emily Drabant; Ripke, Stephan; Wray, Naomi R.; Lewis, Cathryn M.; Hamilton, Steven P.; Weissman, Myrna M.; Breen, Gerome; Byrne, Enda M.; Blackwood, Douglas H.R.; Boomsma, Dorret I.; Cichon, Sven; Heath, Andrew C.; Holsboer, Florian; Lucae, Susanne; Madden, Pamela A.F.; Martin, Nicholas G.; McGuffin, Peter; Muglia, Pierandrea; Noethen, Markus M.; Penninx, Brenda P.; Pergadia, Michele L.; Potash, James B.; Rietschel, Marcella; Lin, Danyu; Müller-Myhsok, Bertram; Shi, Jianxin; Steinberg, Stacy; Grabe, Hans J.; Lichtenstein, Paul; Magnusson, Patrik; Perlis, Roy H.; Preisig, Martin; Smoller, Jordan W.; Stefansson, Kari; Uher, Rudolf; Kutalik, Zoltan; Tansey, Katherine E.; Teumer, Alexander; Viktorin, Alexander; Barnes, Michael R.; Bettecken, Thomas; Binder, Elisabeth B.; Breuer, René; Castro, Victor M.; Churchill, Susanne E.; Coryell, William H.; Craddock, Nick; Craig, Ian W.; Czamara, Darina; De Geus, Eco J.; Degenhardt, Franziska; Farmer, Anne E.; Fava, Maurizio; Frank, Josef; Gainer, Vivian S.; Gallagher, Patience J.; Gordon, Scott D.; Goryachev, Sergey; Gross, Magdalena; Guipponi, Michel; Henders, Anjali K.; Herms, Stefan; Hickie, Ian B.; Hoefels, Susanne; Hoogendijk, Witte; Hottenga, Jouke Jan; Iosifescu, Dan V.; Ising, Marcus; Jones, Ian; Jones, Lisa; Jung-Ying, Tzeng; Knowles, James A.; Kohane, Isaac S.; Kohli, Martin A.; Korszun, Ania; Landen, Mikael; Lawson, William B.; Lewis, Glyn; MacIntyre, Donald; Maier, Wolfgang; Mattheisen, Manuel; McGrath, Patrick J.; McIntosh, Andrew; McLean, Alan; Middeldorp, Christel M.; Middleton, Lefkos; Montgomery, Grant M.; Murphy, Shawn N.; Nauck, Matthias; Nolen, Willem A.; Nyholt, Dale R.; O’Donovan, Michael; Oskarsson, Högni; Pedersen, Nancy; Scheftner, William A.; Schulz, Andrea; Schulze, Thomas G.; Shyn, Stanley I.; Sigurdsson, Engilbert; Slager, Susan L.; Smit, Johannes H.; Stefansson, Hreinn; Steffens, Michael; Thorgeirsson, Thorgeir; Tozzi, Federica; Treutlein, Jens; Uhr, Manfred; van den Oord, Edwin J.C.G.; Van Grootheest, Gerard; Völzke, Henry; Weilburg, Jeffrey B.; Willemsen, Gonneke; Zitman, Frans G.; Neale, Benjamin; Daly, Mark; Levinson, Douglas F.; Sullivan, Patrick F.; Ruepp, Andreas; Müller-Myhsok, Bertram; Hariri, Ahmad R.; Binder, Elisabeth B.

    2015-01-01

    Summary Depression risk is exacerbated by genetic factors and stress exposure; however, the biological mechanisms through which these factors interact to confer depression risk are poorly understood. One putative biological mechanism implicates variability in the ability of cortisol, released in response to stress, to trigger a cascade of adaptive genomic and non-genomic processes through glucocorticoid receptor (GR) activation. Here, we demonstrate that common genetic variants in long-range enhancer elements modulate the immediate transcriptional response to GR activation in human blood cells. These functional genetic variants increase risk for depression and co-heritable psychiatric disorders. Moreover, these risk variants are associated with inappropriate amygdala reactivity, a transdiagnostic psychiatric endophenotype and an important stress hormone response trigger. Network modeling and animal experiments suggest that these genetic differences in GR-induced transcriptional activation may mediate the risk for depression and other psychiatric disorders by altering a network of functionally related stress-sensitive genes in blood and brain. Video Abstract PMID:26050039

  12. Characterization of a cultured human T-cell line with genetically altered ribonucleotide reductase activity. Model for immunodeficiency.

    Science.gov (United States)

    Waddell, D; Ullman, B

    1983-04-10

    From human CCRF-CEM T-cells growing in continuous culture, we have selected, isolated, and characterized a clonal cell line, APHID-D2, with altered ribonucleotide reductase activity. In comparative growth rate experiments, the APHID-D2 cell line is less sensitive than the parental cell line to growth inhibition by deoxyadenosine in the presence of 10 microM erythro-9-(2-hydroxy-3-nonyl)adenine, an inhibitor of adenosine deaminase. The APHID-D2 cell line has elevated levels of all four dNTPs. The resistance of the APHID-D2 cell line to growth inhibition by deoxyadenosine and the abnormal dNTP levels can be explained by the fact that the APHID-D2 ribonucleotide reductase, unlike the parental ribonucleotide reductase, is not normally sensitive to inhibition by dATP. These results suggest that the allosteric site of ribonucleotide reductase which binds both dATP and ATP is altered in the APHID-D2 line. The isolation of a mutant clone of human T-cells which contains a ribonucleotide reductase that has lost its normal sensitivity to dATP and which is resistant to deoxyadenosine-mediated growth inhibition suggests that a primary pathogenic target of accumulated dATP in lymphocytes from patients with adenosine deaminase deficiency may be the cellular ribonucleotide reductase.

  13. Molecular alterations and biomarkers in colorectal cancer

    Science.gov (United States)

    Grady, William M.; Pritchard, Colin C.

    2013-01-01

    The promise of precision medicine is now a clinical reality. Advances in our understanding of the molecular genetics of colorectal cancer genetics is leading to the development of a variety of biomarkers that are being used as early detection markers, prognostic markers, and markers for predicting treatment responses. This is no more evident than in the recent advances in testing colorectal cancers for specific molecular alterations in order to guide treatment with the monoclonal antibody therapies cetuximab and panitumumab, which target the epidermal growth factor receptor (EGFR). In this review, we update a prior review published in 2010 and describe our current understanding of the molecular pathogenesis of colorectal cancer and how these alterations relate to emerging biomarkers for early detection and risk stratification (diagnostic markers), prognosis (prognostic markers), and the prediction of treatment responses (predictive markers). PMID:24178577

  14. Genetic analysis of central carbon metabolism unveils an amino acid substitution that alters maize NAD-dependent isocitrate dehydrogenase activity.

    Directory of Open Access Journals (Sweden)

    Nengyi Zhang

    2010-04-01

    Full Text Available Central carbon metabolism (CCM is a fundamental component of life. The participating genes and enzymes are thought to be structurally and functionally conserved across and within species. Association mapping utilizes a rich history of mutation and recombination to achieve high resolution mapping. Therefore, applying association mapping in maize (Zea mays ssp. mays, the most diverse model crop species, to study the genetics of CCM is a particularly attractive system.We used a maize diversity panel to test the CCM functional conservation. We found heritable variation in enzyme activity for every enzyme tested. One of these enzymes was the NAD-dependent isocitrate dehydrogenase (IDH, E.C. 1.1.1.41, in which we identified a novel amino-acid substitution in a phylogenetically conserved site. Using candidate gene association mapping, we identified that this non-synonymous polymorphism was associated with IDH activity variation. The proposed mechanism for the IDH activity variation includes additional components regulating protein level. With the comparison of sequences from maize and teosinte (Zea mays ssp. Parviglumis, the maize wild ancestor, we found that some CCM genes had also been targeted for selection during maize domestication.Our results demonstrate the efficacy of association mapping for dissecting natural variation in primary metabolic pathways. The considerable genetic diversity observed in maize CCM genes underlies heritable phenotypic variation in enzyme activities and can be useful to identify putative functional sites.

  15. Intelligent and robust prediction of short term wind power using genetic programming based ensemble of neural networks

    International Nuclear Information System (INIS)

    Zameer, Aneela; Arshad, Junaid; Khan, Asifullah; Raja, Muhammad Asif Zahoor

    2017-01-01

    Highlights: • Genetic programming based ensemble of neural networks is employed for short term wind power prediction. • Proposed predictor shows resilience against abrupt changes in weather. • Genetic programming evolves nonlinear mapping between meteorological measures and wind-power. • Proposed approach gives mathematical expressions of wind power to its independent variables. • Proposed model shows relatively accurate and steady wind-power prediction performance. - Abstract: The inherent instability of wind power production leads to critical problems for smooth power generation from wind turbines, which then requires an accurate forecast of wind power. In this study, an effective short term wind power prediction methodology is presented, which uses an intelligent ensemble regressor that comprises Artificial Neural Networks and Genetic Programming. In contrast to existing series based combination of wind power predictors, whereby the error or variation in the leading predictor is propagated down the stream to the next predictors, the proposed intelligent ensemble predictor avoids this shortcoming by introducing Genetical Programming based semi-stochastic combination of neural networks. It is observed that the decision of the individual base regressors may vary due to the frequent and inherent fluctuations in the atmospheric conditions and thus meteorological properties. The novelty of the reported work lies in creating ensemble to generate an intelligent, collective and robust decision space and thereby avoiding large errors due to the sensitivity of the individual wind predictors. The proposed ensemble based regressor, Genetic Programming based ensemble of Artificial Neural Networks, has been implemented and tested on data taken from five different wind farms located in Europe. Obtained numerical results of the proposed model in terms of various error measures are compared with the recent artificial intelligence based strategies to demonstrate the

  16. Prediction of breeding values and selection responses with genetic heterogeneity of environmental variance

    NARCIS (Netherlands)

    Mulder, H.A.; Bijma, P.; Hill, W.G.

    2007-01-01

    There is empirical evidence that genotypes differ not only in mean, but also in environmental variance of the traits they affect. Genetic heterogeneity of environmental variance may indicate genetic differences in environmental sensitivity. The aim of this study was to develop a general framework

  17. Genetic Vulnerability Interacts with Parenting and Early Care and Education to Predict Increasing Externalizing Behavior

    Science.gov (United States)

    Lipscomb, Shannon T.; Laurent, Heidemarie; Neiderhiser, Jenae M.; Shaw, Daniel S.; Natsuaki, Misaki N.; Reiss, David; Leve, Leslie D.

    2014-01-01

    The current study examined interactions among genetic influences and children's early environments on the development of externalizing behaviors from 18 months to 6 years of age. Participants included 233 families linked through adoption (birth parents and adoptive families). Genetic influences were assessed by birth parent temperamental…

  18. Genetic testing to predict sudden cardiac death: current perspectives and future goals

    Directory of Open Access Journals (Sweden)

    Silvia G. Priori

    2014-01-01

    Full Text Available It is known that monogenic traits may predispose young and otherwise healthy individuals to die suddenly. Diseases such as Long QT Syndrome, Brugada Syndrome and Arrhythmogenic Right Ventricular Cardiomyopathy are well known causes of arrhythmic death in young individuals. For several years the concept of “genetic predisposition” to sudden cardiac death has been limited to these uncommon diseases. In the last few years clinical data have supported the view that risk of dying suddenly may cluster in families, supporting the hypothesis of a genetic component for sudden cardiac death. In this review I will try to provide an overview of current knowledge about genetics of sudden death. I will approach this topic by discussing first where we stand in the use of genetics for risk stratification and therapy selection in monogenic diseases and I will then move to discuss the contribution of genetics to patient profiling in acquired cardiovascular diseases.

  19. PREDICTIVE CONTROL OF A BATCH POLYMERIZATION SYSTEM USING A FEEDFORWARD NEURAL NETWORK WITH ONLINE ADAPTATION BY GENETIC ALGORITHM

    OpenAIRE

    Cancelier, A.; Claumann, C. A.; Bolzan, A.; Machado, R. A. F.

    2016-01-01

    Abstract This study used a predictive controller based on an empirical nonlinear model comprising a three-layer feedforward neural network for temperature control of the suspension polymerization process. In addition to the offline training technique, an algorithm was also analyzed for online adaptation of its parameters. For the offline training, the network was statically trained and the genetic algorithm technique was used in combination with the least squares method. For online training, ...

  20. A grand canonical genetic algorithm for the prediction of multi-component phase diagrams and testing of empirical potentials

    International Nuclear Information System (INIS)

    Tipton, William W; Hennig, Richard G

    2013-01-01

    We present an evolutionary algorithm which predicts stable atomic structures and phase diagrams by searching the energy landscape of empirical and ab initio Hamiltonians. Composition and geometrical degrees of freedom may be varied simultaneously. We show that this method utilizes information from favorable local structure at one composition to predict that at others, achieving far greater efficiency of phase diagram prediction than a method which relies on sampling compositions individually. We detail this and a number of other efficiency-improving techniques implemented in the genetic algorithm for structure prediction code that is now publicly available. We test the efficiency of the software by searching the ternary Zr–Cu–Al system using an empirical embedded-atom model potential. In addition to testing the algorithm, we also evaluate the accuracy of the potential itself. We find that the potential stabilizes several correct ternary phases, while a few of the predicted ground states are unphysical. Our results suggest that genetic algorithm searches can be used to improve the methodology of empirical potential design. (paper)

  1. A grand canonical genetic algorithm for the prediction of multi-component phase diagrams and testing of empirical potentials.

    Science.gov (United States)

    Tipton, William W; Hennig, Richard G

    2013-12-11

    We present an evolutionary algorithm which predicts stable atomic structures and phase diagrams by searching the energy landscape of empirical and ab initio Hamiltonians. Composition and geometrical degrees of freedom may be varied simultaneously. We show that this method utilizes information from favorable local structure at one composition to predict that at others, achieving far greater efficiency of phase diagram prediction than a method which relies on sampling compositions individually. We detail this and a number of other efficiency-improving techniques implemented in the genetic algorithm for structure prediction code that is now publicly available. We test the efficiency of the software by searching the ternary Zr-Cu-Al system using an empirical embedded-atom model potential. In addition to testing the algorithm, we also evaluate the accuracy of the potential itself. We find that the potential stabilizes several correct ternary phases, while a few of the predicted ground states are unphysical. Our results suggest that genetic algorithm searches can be used to improve the methodology of empirical potential design.

  2. Temporal and seasonal changes of genetic polymorphisms associated with altered drug susceptibility to chloroquine, lumefantrine and quinine in Guinea-Bissau between 2003 and 2012

    DEFF Research Database (Denmark)

    Jovel, Irina Tatiana; Kofoed, Poul-Erik; Rombo, Lars

    2015-01-01

    BACKGROUND: Guinea-Bissau, West-Africa introduced artemether-lumefantrine in 2008 but quinine has also been commonly prescribed for treatment of uncomplicated Plasmodium falciparum malaria. An efficacious high-dose chloroquine treatment regimen was used previously. Temporal and seasonal changes...... of genetic polymorphisms associated with altered drug susceptibility to chloroquine, lumefantrine and quinine are described. METHODS: Pfcrt K76T, pfmdr1 gene copy numbers, N86Y, Y184F and 1034-1246 sequences were determined using PCR-based methods. Blood samples came from virtually all (n=1806) children aged.......001). CONCLUSIONS: Following the discontinuation of an effective chloroquine regimen highly artemether-lumefantrine susceptible P. falciparum (with pfcrt 76T) accumulated possibly due to suboptimal use of quinine and despite a fitness cost linked to 76T....

  3. Prediction of composite fatigue life under variable amplitude loading using artificial neural network trained by genetic algorithm

    Science.gov (United States)

    Rohman, Muhamad Nur; Hidayat, Mas Irfan P.; Purniawan, Agung

    2018-04-01

    Neural networks (NN) have been widely used in application of fatigue life prediction. In the use of fatigue life prediction for polymeric-base composite, development of NN model is necessary with respect to the limited fatigue data and applicable to be used to predict the fatigue life under varying stress amplitudes in the different stress ratios. In the present paper, Multilayer-Perceptrons (MLP) model of neural network is developed, and Genetic Algorithm was employed to optimize the respective weights of NN for prediction of polymeric-base composite materials under variable amplitude loading. From the simulation result obtained with two different composite systems, named E-glass fabrics/epoxy (layups [(±45)/(0)2]S), and E-glass/polyester (layups [90/0/±45/0]S), NN model were trained with fatigue data from two different stress ratios, which represent limited fatigue data, can be used to predict another four and seven stress ratios respectively, with high accuracy of fatigue life prediction. The accuracy of NN prediction were quantified with the small value of mean square error (MSE). When using 33% from the total fatigue data for training, the NN model able to produce high accuracy for all stress ratios. When using less fatigue data during training (22% from the total fatigue data), the NN model still able to produce high coefficient of determination between the prediction result compared with obtained by experiment.

  4. Targeted sequencing identifies genetic alterations that confer primary resistance to EGFR tyrosine kinase inhibitor (Korean Lung Cancer Consortium).

    Science.gov (United States)

    Lim, Sun Min; Kim, Hye Ryun; Cho, Eun Kyung; Min, Young Joo; Ahn, Jin Seok; Ahn, Myung-Ju; Park, Keunchil; Cho, Byoung Chul; Lee, Ji-Hyun; Jeong, Hye Cheol; Kim, Eun Kyung; Kim, Joo-Hang

    2016-06-14

    Non-small-cell lung cancer (NSCLC) patients with activating epidermal growth factor receptor (EGFR) mutations may exhibit primary resistance to EGFR tyrosine kinase inhibitor (TKI). We aimed to examine genomic alterations associated with de novo resistance to gefitinib in a prospective study of NSCLC patients. One-hundred and fifty two patients with activating EGFR mutations were included in this study and 136 patients' tumor sample were available for targeted sequencing of genomic alterations in 22 genes using the Colon and Lung Cancer panel (Ampliseq, Life Technologies). All 132 patients with EGFR mutation were treated with gefitinib for their treatment of advanced NSCLC. Twenty patients showed primary resistance to EGFR TKI, and were classified as non-responders. A total of 543 somatic single-nucleotide variants (498 missense, 13 nonsense) and 32 frameshift insertions/deletions, with a median of 3 mutations per sample. TP53 was most commonly mutated (47%) and mutations in SMAD4 was also common (19%), as well as DDR2 (16%), PIK3CA (15%), STK11 (14%), and BRAF (7%). Genomic mutations in the PI3K/Akt/mTOR pathway were commonly found in non-responders (45%) compared to responders (27%), and they had significantly shorter progression-free survival and overall survival compared to patients without mutations (2.1 vs. 12.8 months, P=0.04, 15.7 vs. not reached, PAkt/mTOR pathway were commonly identified in non-responders and may confer resistance to EGFR TKI. Screening lung adenocarcinoma patients with clinical cancer gene test may aid in selecting out those who show primary resistance to EGFR TKI (NCT01697163).

  5. Prediction of Chemical Carcinogenicity in Rodents from in vitro Genetic Toxicity Assays

    Science.gov (United States)

    Tennant, Raymond W.; Margolin, Barry H.; Shelby, Michael D.; Zeiger, Errol; Haseman, Joseph K.; Spalding, Judson; Caspary, William; Resnick, Michael; Stasiewicz, Stanley; Anderson, Beth; Minor, Robert

    1987-05-01

    Four widely used in vitro assays for genetic toxicity were evaluated for their ability to predict the carcinogenicity of selected chemicals in rodents. These assays were mutagenesis in Salmonella and mouse lymphoma cells and chromosome aberrations and sister chromatid exchanges in Chinese hamster ovary cells. Seventy-three chemicals recently tested in 2-year carcinogenicity studies conducted by the National Cancer Institute and the National Toxicology Program were used in this evaluation. Test results from the four in vitro assays did not show significant differences in individual concordance with the rodent carcinogenicity results; the concordance of each assay was approximately 60 percent. Within the limits of this study there was no evidence of complementarity among the four assays, and no battery of tests constructed from these assays improved substantially on the overall performance of the Salmonella assay. The in vitro assays which represented a range of three cell types and four end points did show substantial agreement among themselves, indicating that chemicals positive in one in vitro assay tended to be positive in the other in vitro assays. To help put this project into its proper context, we emphasize certain features of the study: 1) Standard protocols were used to mimic the major use of STTs worldwide--screening for mutagens and carcinogens; no attempt was made to optimize protocols for specific chemicals. 2) The 73 NTP chemicals and their 60% incidence of carcinogenicity are probably not representative of the universe of chemicals but rather reflect the recent chemical selection process for the NTP carcinogenicity assay. 3) The small, diverse group of chemicals precludes a meaningful evaluation of the predictive utility of chemical structure information. 4) The NTP is currently testing these same 73 chemicals in two in vivo STTs for chromosomal effects. 5) Complete data for an additional group of 30 to 40 NTP chemicals will be gathered on

  6. Genetic deletion of the P2Y2 receptor offers significant resistance to development of lithium-induced polyuria accompanied by alterations in PGE2 signaling.

    Science.gov (United States)

    Zhang, Yue; Pop, Ioana L; Carlson, Noel G; Kishore, Bellamkonda K

    2012-01-01

    Lithium (Li)-induced polyuria is due to resistance of the medullary collecting duct (mCD) to the action of arginine vasopressin (AVP), apparently mediated by increased production of PGE(2). We previously reported that the P2Y(2) receptor (P2Y(2)-R) antagonizes the action of AVP on the mCD and may play a role in Li-induced polyuria by enhancing the production of PGE(2) in mCD. Hence, we hypothesized that genetic deletion of P2Y(2)-R should ameliorate Li-induced polyuria. Wild-type (WT) or P2Y(2)-R knockout (KO) mice were fed normal or Li-added diets for 14 days and euthanized. Li-induced polyuria, and decreases in urine osmolality and AQP2 protein abundance in the renal medulla, were significantly less compared with WT mice despite the lack of differences in Li intake or terminal serum or inner medullary tissue Li levels. Li-induced increased urinary excretion of PGE(2) was not affected in KO mice. However, prostanoid EP(3) receptor (EP3-R) protein abundance in the renal medulla of KO mice was markedly lower vs. WT mice, irrespective of the dietary regimen. The protein abundances of other EP-Rs were not altered across the groups irrespective of the dietary regimen. Ex vivo stimulation of mCD with PGE(2) generated significantly more cAMP in Li-fed KO mice (130%) vs. Li-fed WT mice (100%). Taken together, these data suggest 1) genetic deletion of P2Y(2)-R offers significant resistance to the development of Li-induced polyuria; and 2) this resistance is apparently due to altered PGE(2) signaling mediated by a marked decrease in EP3-R protein abundance in the medulla, thus attenuating the EP3-mediated decrease in cAMP levels in mCD.

  7. The DNA of coral reef biodiversity: predicting and protecting genetic diversity of reef assemblages.

    Science.gov (United States)

    Selkoe, Kimberly A; Gaggiotti, Oscar E; Treml, Eric A; Wren, Johanna L K; Donovan, Mary K; Toonen, Robert J

    2016-04-27

    Conservation of ecological communities requires deepening our understanding of genetic diversity patterns and drivers at community-wide scales. Here, we use seascape genetic analysis of a diversity metric, allelic richness (AR), for 47 reef species sampled across 13 Hawaiian Islands to empirically demonstrate that large reefs high in coral cover harbour the greatest genetic diversity on average. We found that a species's life history (e.g. depth range and herbivory) mediates response of genetic diversity to seascape drivers in logical ways. Furthermore, a metric of combined multi-species AR showed strong coupling to species richness and habitat area, quality and stability that few species showed individually. We hypothesize that macro-ecological forces and species interactions, by mediating species turnover and occupancy (and thus a site's mean effective population size), influence the aggregate genetic diversity of a site, potentially allowing it to behave as an apparent emergent trait that is shaped by the dominant seascape drivers. The results highlight inherent feedbacks between ecology and genetics, raise concern that genetic resilience of entire reef communities is compromised by factors that reduce coral cover or available habitat, including thermal stress, and provide a foundation for new strategies for monitoring and preserving biodiversity of entire reef ecosystems. © 2016 The Authors.

  8. The relative abundance of predicted genes associated with ammonia-oxidation, nitrate reduction, and biomass decomposition in mineral soil are altered by intensive timber harvest.

    Science.gov (United States)

    Mushinski, R. M.; Zhou, Y.; Gentry, T. J.; Boutton, T. W.

    2017-12-01

    Forest ecosystems in the southern United States are substantially altered by anthropogenic disturbances such as timber harvest and land conversion, with effects being observed in carbon and nutrient pools as well as biogeochemical processes. Furthermore, the desire to develop renewable energy sources in the form of biomass extraction from logging residues may result in alterations in soil community structure and function. While the impact of forest management on soil physicochemical properties of the region has been studied, its' long-term effect on soil bacterial community composition and metagenomic potential is relatively unknown, especially at deeper soil depths. This study investigates how intensive organic matter removal intensities associated with timber harvest influence decadal-scale alterations in bacterial community structure and functional potential in the upper 1-m of the soil profile, 18 years post-harvest in a Pinus taeda L. forest of eastern Texas. Amplicon sequencing of the 16S rRNA gene was used in conjunction with soil chemical analyses to evaluate treatment-induced differences in community composition and potential environmental drivers of associated change. Furthermore, functional potential was assessed by using amplicon data to make metagenomic predictions. Results indicate that increasing organic matter removal intensity leads to altered community composition and the relative abundance of dominant OTUs annotated to Burkholderia and Aciditerrimonas. The relative abundance of predicted genes associated with dissimilatory nitrate reduction and denitrification were highest in the most intensively harvested treatment while genes involved in nitrification were significantly lower in the most intensively harvested treatment. Furthermore, genes associated with glycosyltransferases were significantly reduced with increasing harvest intensity while polysaccharide lyases increased. These results imply that intensive organic matter removal may create

  9. Early Prediction of Sepsis Incidence in Critically Ill Patients Using Specific Genetic Polymorphisms.

    Science.gov (United States)

    David, Vlad Laurentiu; Ercisli, Muhammed Furkan; Rogobete, Alexandru Florin; Boia, Eugen S; Horhat, Razvan; Nitu, Razvan; Diaconu, Mircea M; Pirtea, Laurentiu; Ciuca, Ioana; Horhat, Delia; Horhat, Florin George; Licker, Monica; Popovici, Sonia Elena; Tanasescu, Sonia; Tataru, Calin

    2017-06-01

    Several diagnostic methods for the evaluation and monitoring were used to find out the pro-inflammatory status, as well as incidence of sepsis in critically ill patients. One such recent method is based on investigating the genetic polymorphisms and determining the molecular and genetic links between them, as well as other sepsis-associated pathophysiologies. Identification of genetic polymorphisms in critical patients with sepsis can become a revolutionary method for evaluating and monitoring these patients. Similarly, the complications, as well as the high costs associated with the management of patients with sepsis, can be significantly reduced by early initiation of intensive care.

  10. Prediction of warfarin maintenance dose in Han Chinese patients using a mechanistic model based on genetic and non-genetic factors.

    Science.gov (United States)

    Lu, Yuan; Yang, Jinbo; Zhang, Haiyan; Yang, Jin

    2013-07-01

    Many attempts have been made to predict the warfarin maintenance dose in patients beginning warfarin therapy using a descriptive model based on multiple linear regression. Here we report the first attempt to develop a comprehensive mechanistic model integrating in vitro-in vivo extrapolation (IVIVE) with a pharmacokinetic-pharmacodynamic model to predict the warfarin maintenance dose in Han Chinese patients. The model incorporates demographic factors [sex, age, body weight (BW)] and the genetic polymorphisms of cytochrome P450 (CYP) 2C9 (CYP2C9) and vitamin K epoxide reductase complex subunit 1 (VKORC1). Information on the various factors, mean warfarin daily dose and International Normalized Ratio (INR) was available for a cohort of 197 Han Chinese patients. Based on in vitro enzyme kinetic parameters for S-warfarin metabolism, demographic data for Han Chinese and some scaling factors, the S-warfarin clearance (CL) was predicted for patients in the cohort with different CYP2C9 genotypes using IVIVE. The plasma concentration of S-warfarin after a single oral dose was simulated using a one-compartment pharmacokinetic model with first-order absorption and a lag time and was combined with a mechanistic coagulation model to simulate the INR response. The warfarin maintenance dose was then predicted based on the demographic data and genotypes of CYP2C9 and VKORC1 for each patient and using the observed steady-state INR (INRss) as a target value. Finally, sensitivity analysis was carried out to determine which factor(s) affect the warfarin maintenance dose most strongly. The predictive performance of this mechanistic model is not inferior to that of our previous descriptive model. There were significant differences in the mean warfarin daily dose in patients with different CYP2C9 and VKORC1 genotypes. Using IVIVE, the predicted mean CL of S-warfarin for patients with CYP2C9*1/*3 (0.092 l/h, n = 11) was 57 % less than for those with wild-type *1/*1 (0.215 l/h, n

  11. Predicting the effect of naltrexone and acamprosate in alcohol-dependent patients using genetic indicators

    NARCIS (Netherlands)

    Ooteman, Wendy; Naassila, Mickaël; Koeter, Maarten W. J.; Verheul, Roel; Schippers, Gerard M.; Houchi, Hakim; Daoust, Martine; van den Brink, Wim

    2009-01-01

    Acamprosate and naltrexone are effective medications in the treatment of alcoholism. However. effect sizes are modest. Pharmacogenomics may improve patient-treatment-matching and effect sizes. It is hypothesized that naltrexone exerts its effect through genetic characteristics associated with the

  12. Resource allocation for maximizing prediction accuracy and genetic gain of genomic selection in plant breeding: a simulation experiment.

    Science.gov (United States)

    Lorenz, Aaron J

    2013-03-01

    Allocating resources between population size and replication affects both genetic gain through phenotypic selection and quantitative trait loci detection power and effect estimation accuracy for marker-assisted selection (MAS). It is well known that because alleles are replicated across individuals in quantitative trait loci mapping and MAS, more resources should be allocated to increasing population size compared with phenotypic selection. Genomic selection is a form of MAS using all marker information simultaneously to predict individual genetic values for complex traits and has widely been found superior to MAS. No studies have explicitly investigated how resource allocation decisions affect success of genomic selection. My objective was to study the effect of resource allocation on response to MAS and genomic selection in a single biparental population of doubled haploid lines by using computer simulation. Simulation results were compared with previously derived formulas for the calculation of prediction accuracy under different levels of heritability and population size. Response of prediction accuracy to resource allocation strategies differed between genomic selection models (ridge regression best linear unbiased prediction [RR-BLUP], BayesCπ) and multiple linear regression using ordinary least-squares estimation (OLS), leading to different optimal resource allocation choices between OLS and RR-BLUP. For OLS, it was always advantageous to maximize population size at the expense of replication, but a high degree of flexibility was observed for RR-BLUP. Prediction accuracy of doubled haploid lines included in the training set was much greater than of those excluded from the training set, so there was little benefit to phenotyping only a subset of the lines genotyped. Finally, observed prediction accuracies in the simulation compared well to calculated prediction accuracies, indicating these theoretical formulas are useful for making resource allocation

  13. How closely does genetic diversity in finite populations conform to predictions of neutral theory? Large deficits in regions of low recombination.

    Science.gov (United States)

    Frankham, R

    2012-03-01

    Levels of genetic diversity in finite populations are crucial in conservation and evolutionary biology. Genetic diversity is required for populations to evolve and its loss is related to inbreeding in random mating populations, and thus to reduced population fitness and increased extinction risk. Neutral theory is widely used to predict levels of genetic diversity. I review levels of genetic diversity in finite populations in relation to predictions of neutral theory. Positive associations between genetic diversity and population size, as predicted by neutral theory, are observed for microsatellites, allozymes, quantitative genetic variation and usually for mitochondrial DNA (mtDNA). However, there are frequently significant deviations from neutral theory owing to indirect selection at linked loci caused by balancing selection, selective sweeps and background selection. Substantially lower genetic diversity than predicted under neutrality was found for chromosomes with low recombination rates and high linkage disequilibrium (compared with 'normally' recombining chromosomes within species and adjusted for different copy numbers and mutation rates), including W (median 100% lower) and Y (89% lower) chromosomes, dot fourth chromosomes in Drosophila (94% lower) and mtDNA (67% lower). Further, microsatellite genetic and allelic diversity were lost at 12 and 33% faster rates than expected in populations adapting to captivity, owing to widespread selective sweeps. Overall, neither neutral theory nor most versions of the genetic draft hypothesis are compatible with all empirical results.

  14. Genetic alterations of the long terminal repeat of an ecotropic porcine endogenous retrovirus during passage in human cells

    International Nuclear Information System (INIS)

    Denner, Joachim; Specke, Volker; Thiesen, Ulla; Karlas, Alexander; Kurth, Reinhard

    2003-01-01

    Human-tropic porcine endogenous retroviruses (PERV) such as PERV-A and PERV-B can infect human cells and are therefore a potential risk to recipients of xenotransplants. A similar risk is posed by recombinant viruses containing the receptor-binding site of PERV-A and large parts of the genome of the ecotropic PERV-C including its long terminal repeat (LTR). We describe here the unique organization of the PERV-C LTR and its changes during serial passage of recombinant virus in human cells. An increase in virus titer correlated with an increase in LTR length, caused by multiplication of 37-bp repeats containing nuclear factor Y binding sites. Luciferase dual reporter assays revealed a correlation between the number of repeats and the extent of expression. No alterations have been observed in the receptor-binding site, indicating that the increased titer is due to the changes in the LTR. These data indicate that recombinant PERVs generated during infection of human cells can adapt and subsequently replicate with greater efficiency

  15. Epidermal growth factor receptor signaling pathway is frequently altered in ampullary carcinoma at protein and genetic levels.

    Science.gov (United States)

    Mikhitarian, Kaidi; Pollen, Maressa; Zhao, Zhiguo; Shyr, Yu; Merchant, Nipun B; Parikh, Alexander; Revetta, Frank; Washington, M Kay; Vnencak-Jones, Cindy; Shi, Chanjuan

    2014-05-01

    Our objective was to explore alteration of the epidermal growth factor receptor (EGFR) signaling pathway in ampullary carcinoma. Immunohistochemical studies were employed to evaluate expression of amphiregulin as well as expression and activation of EGFR. A lab-developed assay was used to identify mutations in the EGFR pathway genes, including KRAS, BRAF, PIK3CA, PTEN, and AKT1. A total of 52 ampullary carcinomas were identified, including 25 intestinal-type and 24 pancreatobiliary-type tumors, with the intestinal type being associated with a younger age at diagnosis (P=0.03) and a better prognosis (PSMAD4 and BRAF. KRAS mutations at codons 12 and 13 did not adversely affect overall survival. In conclusion, EGFR expression and activation were different between intestinal- and pancreatobiliary-type ampullary carcinoma. KRAS mutation was common in both histologic types; however, the incidence appeared to be lower in the pancreatobiliary type compared with its pancreatic counterpart, pancreatic ductal adenocarcinoma. Mutational analysis of the EGFR pathway genes may provide important insights into personalized treatment for patients with ampullary carcinoma.

  16. Clinical characterization of a novel calcium sensing receptor genetic alteration in a Greek patient with autosomal dominant hypocalcemia type 1.

    Science.gov (United States)

    Papadopoulou, Anna; Gole, Evangelia; Melachroinou, Katerina; Trangas, Theoni; Bountouvi, Evaggelia; Papadimitriou, Anastasios

    2017-04-01

    Autosomal dominant hypocalcemia (ADH) is a rare familial or sporadic syndrome associated with activating mutations in the calcium sensing receptor (CaSR) gene. The aim of this study was to assess the functional significance of a novel CaSR mutation and, moreover, to present the clinical characteristics and the bone mineral density (BMD) progression from early childhood to late puberty in a patient with ADH. Genetic analysis of the CaSR gene was performed in a patient who presented in the neonatal period with hypocalcemic seizures and biochemical features of ADH. The functional impact of the novel mutation identified was assessed in cultured HEK 293T cells, transfected with either the wild type (WT) or mutant CaSR, by evaluating intracellular calcium ([Ca2+]i) influx after stimulation with extracellular calcium (Ca2+). Several BMD measurements were performed during the patient's follow-up until late puberty. A novel CaSR mutation (p.L123S) was identified, which, as demonstrated by functional analysis, renders CaSR more sensitive to extracellular changes of Ca2+ compared with the WT, although the difference is not statistically significant. BMD measurements, from early childhood to late puberty, revealed high normal to elevated BMD. We present the first Greek patient, to our knowledge, with sporadic ADH due to a novel gain-of-function mutation of the CaSR gene.

  17. Evaluation of the genetic alterations in direct and indirect exposures of hexavalent chromium [Cr(VI)] in leather tanning industry workers North Arcot District, South India.

    Science.gov (United States)

    Balachandar, Vellingiri; Arun, Meyyazhagan; Mohana Devi, Subramaniam; Velmurugan, Palanivel; Manikantan, Pappusamy; Karthick Kumar, Alagamuthu; Sasikala, Keshavarao; Venkatesan, Chinnakulandai

    2010-10-01

    The focal aim of the present study was to identify the genetic alterations occurring in the tannery workers and surrounding inhabitants chronically exposed to hexavalent chromium [Cr(VI)]. A total of 108 samples which includes 72 exposed subjects [36 directly exposed (DE) subjects and 36 indirectly exposed (IE) subjects] and 36 controls were recruited for this study. The exposed subjects and controls were selected based on the Cr level present in air and their urine. Directly exposed subjects were categorized based on their work duration in the tannery industries, whereas the indirectly exposed subjects were categorized based on their year of residence in the place adjacent to tannery industries for more than 3 decades. Controls were normal and healthy. Age was matched for the exposed subjects and controls. The exposed subjects as well as the controls were categorized based on their age (group I, 41 years). Cell cultures were established from blood samples (5 ml from each subject) collected from the subjects (exposed subjects and controls) after obtaining informed consent. G-banding (Giemsa staining) of the cultures, micronucleus (MN) assay and comet assay were used to identify the genetic alterations of individuals exposed to Cr(VI) in comparison with the controls. A higher degree of total CA [12 ± 8.49 (21-25 years)] and MN [18.69 ± 7.39 (11-15 years)] was found in DE subjects compared to other groups. In IE subjects, elevated levels of CA [5.67 ± 1.15 (51-60 years)] and MN [25 ± 9.89 (71-80 years)] were observed. As expected, controls exhibited minimal number of alterations. The overall CA frequency due to Cr exposure was significantly different from that of the controls for both chromatid and chromosome type aberrations (P < 0.05 by ANOVA). The MN/1,000 binucleated cells were significantly increased (P < 0.05) in the peripheral lymphocytes of DE and IE subjects in comparison with controls. The mean tail length of comet assay for DE, IE and controls were

  18. Predictive value of testing for multiple genetic variants in multifactorial diseases: implications for the discourse on ethical, legal and social issues

    Directory of Open Access Journals (Sweden)

    A. Cecile J.W. Janssens

    2006-12-01

    Full Text Available Multifactorial diseases such as type 2 diabetes, osteoporosis, and cardiovascular disease are caused by a complex interplay of many genetic and nongenetic factors, each of which conveys a minor increase in the risk of disease. Unraveling the genetic origins of these diseases is expected to lead to individualized medicine, in which the prevention and treatment strategies are personalized on the basis of the results of predictive genetic tests. This great optimism is counterbalanced by concerns about the ethical, legal, and social implications of genomic medicine, such as the protection of privacy and autonomy, stigmatization, discrimination, and the psychological burden of genetic testing. These concerns are translated from genetic testing in monogenic disorders, but this translation may not be appropriate. Multiple genetic testing (genomic profiling has essential differences from genetic testing in monogenic disorders. The differences lie in the lower predictive value of the test results, the pleiotropic effects of susceptibility genes, and the low inheritance of genomic profiles. For these reasons, genomic profiling may be more similar to nongenetic tests than to predictive tests for monogenic diseases. Therefore, ethical, legal, and social issues that apply to predictive genetic testing for monogenic diseases may not be relevant for the prediction of multifactorial disorders in genomic medicine.

  19. A method of predicting changes in human gene splicing induced by genetic variants in context of cis-acting elements

    Directory of Open Access Journals (Sweden)

    Hicks Chindo

    2010-01-01

    Full Text Available Abstract Background Polymorphic variants and mutations disrupting canonical splicing isoforms are among the leading causes of human hereditary disorders. While there is a substantial evidence of aberrant splicing causing Mendelian diseases, the implication of such events in multi-genic disorders is yet to be well understood. We have developed a new tool (SpliceScan II for predicting the effects of genetic variants on splicing and cis-regulatory elements. The novel Bayesian non-canonical 5'GC splice site (SS sensor used in our tool allows inference on non-canonical exons. Results Our tool performed favorably when compared with the existing methods in the context of genes linked to the Autism Spectrum Disorder (ASD. SpliceScan II was able to predict more aberrant splicing isoforms triggered by the mutations, as documented in DBASS5 and DBASS3 aberrant splicing databases, than other existing methods. Detrimental effects behind some of the polymorphic variations previously associated with Alzheimer's and breast cancer could be explained by changes in predicted splicing patterns. Conclusions We have developed SpliceScan II, an effective and sensitive tool for predicting the detrimental effects of genomic variants on splicing leading to Mendelian and complex hereditary disorders. The method could potentially be used to screen resequenced patient DNA to identify de novo mutations and polymorphic variants that could contribute to a genetic disorder.

  20. Biopsychosocial influence on exercise-induced injury: genetic and psychological combinations are predictive of shoulder pain phenotypes.

    Science.gov (United States)

    George, Steven Z; Parr, Jeffrey J; Wallace, Margaret R; Wu, Samuel S; Borsa, Paul A; Dai, Yunfeng; Fillingim, Roger B

    2014-01-01

    Chronic pain is influenced by biological, psychological, social, and cultural factors. The current study investigated potential roles for combinations of genetic and psychological factors in the development and/or maintenance of chronic musculoskeletal pain. An exercise-induced shoulder injury model was used, and a priori selected genetic (ADRB2, COMT, OPRM1, AVPR1 A, GCH1, and KCNS1) and psychological (anxiety, depressive symptoms, pain catastrophizing, fear of pain, and kinesiophobia) factors were included as predictors. Pain phenotypes were shoulder pain intensity (5-day average and peak reported on numerical rating scale), upper extremity disability (5-day average and peak reported on the QuickDASH), and shoulder pain duration (in days). After controlling for age, sex, and race, the genetic and psychological predictors were entered as main effects and interaction terms in separate regression models for the different pain phenotypes. Results from the recruited cohort (N = 190) indicated strong statistical evidence for interactions between the COMT diplotype and 1) pain catastrophizing for 5-day average upper extremity disability and 2) depressive symptoms for pain duration. There was moderate statistical evidence for interactions for other shoulder pain phenotypes between additional genes (ADRB2, AVPR1 A, and KCNS1) and depressive symptoms, pain catastrophizing, or kinesiophobia. These findings confirm the importance of the combined predictive ability of COMT with psychological distress and reveal other novel combinations of genetic and psychological factors that may merit additional investigation in other pain cohorts. Interactions between genetic and psychological factors were investigated as predictors of different exercise-induced shoulder pain phenotypes. The strongest statistical evidence was for interactions between the COMT diplotype and pain catastrophizing (for upper extremity disability) or depressive symptoms (for pain duration). Other novel

  1. Improved prediction of genetic predisposition to psychiatric disorders using genomic feature best linear unbiased prediction models

    DEFF Research Database (Denmark)

    Rohde, Palle Duun; Demontis, Ditte; Børglum, Anders

    is enriched for causal variants. Here we apply the GFBLUP model to a small schizophrenia case-control study to test the promise of this model on psychiatric disorders, and hypothesize that the performance will be increased when applying the model to a larger ADHD case-control study if the genomic feature...... contains the causal variants. Materials and Methods: The schizophrenia study consisted of 882 controls and 888 schizophrenia cases genotyped for 520,000 SNPs. The ADHD study contained 25,954 controls and 16,663 ADHD cases with 8,4 million imputed genotypes. Results: The predictive ability for schizophrenia.......6% for the null model). Conclusion: The improvement in predictive ability for schizophrenia was marginal, however, greater improvement is expected for the larger ADHD data....

  2. Genetic alteration with variable intron/exon organization amongst five PI-homoeologous genes in Platanus acerifolia.

    Science.gov (United States)

    Zhang, Jiaqi; Guo, Cong; Liu, Guofeng; Li, Zhineng; Li, Xiaomei; Bao, Manzhu

    2011-03-01

    Flower development has been extensively characterized in the model species Arabidopsis thaliana and Antirrhinum majus. However, there have been few studies in woody species. Here, we report the isolation and characterization of five PISTILLATA (PI) homoeologous genes (PaPI1-to-5) from the London Plane tree (Platanus acerifolia Willd). PaPI1 and PaPI2 show a similar genomic structure to other known PI homoeologs, but PaPI3/4/5 lack intron sequences. In addition, PaPI5 lacks the third, fourth and fifth exons which encode the K-domain. These altered gene copies may have originated as 'processed' retrogenes. PaPI2 appears micro-regulated by alternative splicing, displaying three splice forms (PaPI2a, PaPI2b and PaPI2c). RT-PCR analysis showed different expression profiles and transcript abundance for the five PaPI genes. PaPI transcripts encoding full-length polypeptides were expressed predominantly in male/female inflorescences and PaPI2a was the most abundant transcript (59%) indicating that PaPI2 may be the major functional PI-homoeolog in London Plane. Phenotypic characterization in a heterologous expression system demonstrated that the full-length PaPI product functions as a B class gene. By contrast the PaPI5 form, which lacks the K-domain, had no apparent effect on flower development. In vitro studies also demonstrated that the K-domain is required to form PaPI/PaAP3 heterodimers. Copyright © 2010 Elsevier B.V. All rights reserved.

  3. Exceptions to the rule: case studies in the prediction of pathogenicity for genetic variants in hereditary cancer genes.

    Science.gov (United States)

    Rosenthal, E T; Bowles, K R; Pruss, D; van Kan, A; Vail, P J; McElroy, H; Wenstrup, R J

    2015-12-01

    Based on current consensus guidelines and standard practice, many genetic variants detected in clinical testing are classified as disease causing based on their predicted impact on the normal expression or function of the gene in the absence of additional data. However, our laboratory has identified a subset of such variants in hereditary cancer genes for which compelling contradictory evidence emerged after the initial evaluation following the first observation of the variant. Three representative examples of variants in BRCA1, BRCA2 and MSH2 that are predicted to disrupt splicing, prematurely truncate the protein, or remove the start codon were evaluated for pathogenicity by analyzing clinical data with multiple classification algorithms. Available clinical data for all three variants contradicts the expected pathogenic classification. These variants illustrate potential pitfalls associated with standard approaches to variant classification as well as the challenges associated with monitoring data, updating classifications, and reporting potentially contradictory interpretations to the clinicians responsible for translating test outcomes to appropriate clinical action. It is important to address these challenges now as the model for clinical testing moves toward the use of large multi-gene panels and whole exome/genome analysis, which will dramatically increase the number of genetic variants identified. © 2015 The Authors. Clinical Genetics published by John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  4. Optimization the Initial Weights of Artificial Neural Networks via Genetic Algorithm Applied to Hip Bone Fracture Prediction

    Directory of Open Access Journals (Sweden)

    Yu-Tzu Chang

    2012-01-01

    Full Text Available This paper aims to find the optimal set of initial weights to enhance the accuracy of artificial neural networks (ANNs by using genetic algorithms (GA. The sample in this study included 228 patients with first low-trauma hip fracture and 215 patients without hip fracture, both of them were interviewed with 78 questions. We used logistic regression to select 5 important factors (i.e., bone mineral density, experience of fracture, average hand grip strength, intake of coffee, and peak expiratory flow rate for building artificial neural networks to predict the probabilities of hip fractures. Three-layer (one hidden layer ANNs models with back-propagation training algorithms were adopted. The purpose in this paper is to find the optimal initial weights of neural networks via genetic algorithm to improve the predictability. Area under the ROC curve (AUC was used to assess the performance of neural networks. The study results showed the genetic algorithm obtained an AUC of 0.858±0.00493 on modeling data and 0.802 ± 0.03318 on testing data. They were slightly better than the results of our previous study (0.868±0.00387 and 0.796±0.02559, resp.. Thus, the preliminary study for only using simple GA has been proved to be effective for improving the accuracy of artificial neural networks.

  5. Environmental gradients predict the genetic population structure of a coral reef fish in the Red Sea

    KAUST Repository

    Nanninga, Gerrit B.

    2014-01-20

    The relatively recent fields of terrestrial landscape and marine seascape genetics seek to identify the influence of biophysical habitat features on the spatial genetic structure of populations or individuals. Over the last few years, there has been accumulating evidence for the effect of environmental heterogeneity on patterns of gene flow and connectivity in marine systems. Here, we investigate the population genetic patterns of an anemonefish, Amphiprion bicinctus, along the Saudi Arabian coast of the Red Sea. We collected nearly one thousand samples from 19 locations, spanning approximately 1500 km, and genotyped them at 38 microsatellite loci. Patterns of gene flow appeared to follow a stepping-stone model along the northern and central Red Sea, which was disrupted by a distinct genetic break at a latitude of approximately 19°N. The Red Sea is characterized by pronounced environmental gradients along its axis, roughly separating the northern and central from the southern basin. Using mean chlorophyll-a concentrations as a proxy for this gradient, we ran tests of isolation by distance (IBD, R2 = 0.52) and isolation by environment (IBE, R2 = 0.64), as well as combined models using partial Mantel tests and multiple matrix regression with randomization (MMRR). We found that genetic structure across our sampling sites may be best explained by a combined model of IBD and IBE (Mantel: R2 = 0.71, MMRR: R2 = 0.86). Our results highlight the potential key role of environmental patchiness in shaping patterns of gene flow in species with pelagic larval dispersal. We support growing calls for the integration of biophysical habitat characteristics into future studies of population genetic structure. © 2014 John Wiley & Sons Ltd.

  6. Environmental gradients predict the genetic population structure of a coral reef fish in the Red Sea

    KAUST Repository

    Nanninga, Gerrit B.; Saenz Agudelo, Pablo; Manica, Andrea; Berumen, Michael L.

    2014-01-01

    The relatively recent fields of terrestrial landscape and marine seascape genetics seek to identify the influence of biophysical habitat features on the spatial genetic structure of populations or individuals. Over the last few years, there has been accumulating evidence for the effect of environmental heterogeneity on patterns of gene flow and connectivity in marine systems. Here, we investigate the population genetic patterns of an anemonefish, Amphiprion bicinctus, along the Saudi Arabian coast of the Red Sea. We collected nearly one thousand samples from 19 locations, spanning approximately 1500 km, and genotyped them at 38 microsatellite loci. Patterns of gene flow appeared to follow a stepping-stone model along the northern and central Red Sea, which was disrupted by a distinct genetic break at a latitude of approximately 19°N. The Red Sea is characterized by pronounced environmental gradients along its axis, roughly separating the northern and central from the southern basin. Using mean chlorophyll-a concentrations as a proxy for this gradient, we ran tests of isolation by distance (IBD, R2 = 0.52) and isolation by environment (IBE, R2 = 0.64), as well as combined models using partial Mantel tests and multiple matrix regression with randomization (MMRR). We found that genetic structure across our sampling sites may be best explained by a combined model of IBD and IBE (Mantel: R2 = 0.71, MMRR: R2 = 0.86). Our results highlight the potential key role of environmental patchiness in shaping patterns of gene flow in species with pelagic larval dispersal. We support growing calls for the integration of biophysical habitat characteristics into future studies of population genetic structure. © 2014 John Wiley & Sons Ltd.

  7. Enrichment of minor allele of SNPs and genetic prediction of type 2 diabetes risk in British population.

    Directory of Open Access Journals (Sweden)

    Xiaoyun Lei

    Full Text Available Type 2 diabetes (T2D is a complex disorder characterized by high blood sugar, insulin resistance, and relative lack of insulin. The collective effects of genome wide minor alleles of common SNPs, or the minor allele content (MAC in an individual, have been linked with quantitative variations of complex traits and diseases. Here we studied MAC in T2D using previously published SNP datasets and found higher MAC in cases relative to matched controls. A set of 357 SNPs was found to have the best predictive accuracy in a British population. A weighted risk score calculated by using this set produced an area under the curve (AUC score of 0.86, which is comparable to risk models built by phenotypic markers. These results identify a novel genetic risk element in T2D susceptibility and provide a potentially useful genetic method to identify individuals with high risk of T2D.

  8. Feline genetics: clinical applications and genetic testing.

    Science.gov (United States)

    Lyons, Leslie A

    2010-11-01

    DNA testing for domestic cat diseases and appearance traits is a rapidly growing asset for veterinary medicine. Approximately 33 genes contain 50 mutations that cause feline health problems or alterations in the cat's appearance. A variety of commercial laboratories can now perform cat genetic diagnostics, allowing both the veterinary clinician and the private owner to obtain DNA test results. DNA is easily obtained from a cat via a buccal swab with a standard cotton bud or cytological brush, allowing DNA samples to be easily sent to any laboratory in the world. The DNA test results identify carriers of the traits, predict the incidence of traits from breeding programs, and influence medical prognoses and treatments. An overall goal of identifying these genetic mutations is the correction of the defect via gene therapies and designer drug therapies. Thus, genetic testing is an effective preventative medicine and a potential ultimate cure. However, genetic diagnostic tests may still be novel for many veterinary practitioners and their application in the clinical setting needs to have the same scrutiny as any other diagnostic procedure. This article will review the genetic tests for the domestic cat, potential sources of error for genetic testing, and the pros and cons of DNA results in veterinary medicine. Highlighted are genetic tests specific to the individual cat, which are a part of the cat's internal genome. Copyright © 2010 Elsevier Inc. All rights reserved.

  9. Prediction of individual genetic risk to prostate cancer using a polygenic score

    DEFF Research Database (Denmark)

    Szulkin, Robert; Whitington, Thomas; Eklund, Martin

    2015-01-01

    BACKGROUND: Polygenic risk scores comprising established susceptibility variants have shown to be informative classifiers for several complex diseases including prostate cancer. For prostate cancer it is unknown if inclusion of genetic markers that have so far not been associated with prostate ca...

  10. Prediction of breast cancer risk based on profiling with common genetic variants

    DEFF Research Database (Denmark)

    Mavaddat, Nasim; Pharoah, Paul D P; Michailidou, Kyriaki

    2015-01-01

    BACKGROUND: Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking. M...

  11. Comparison of collinearity mitigation techniques used in predicting BLUP breeding values and genetic gains over generations

    CSIR Research Space (South Africa)

    Eatwell, KA

    2011-01-01

    Full Text Available techniques and of two computational numerical precisions on the genetic gains in breeding populations. Multiple-trait, multiple-trial BLUP selection scenarios were run on Eucalyptus grandis (F1, F2 and F3) and Pinus patula (F1 and F2) data, comparing...

  12. Cell wall peptidolipids of Mycobacterium avium: from genetic prediction to exact structure of a nonribosomal peptide

    Science.gov (United States)

    Total lipids from an M. avium subsp. paratuberculosis (Map) ovine strain (S-type) contained no identifiable glycopeptidolipids or lipopentapeptide, yet both lipids are present in other M. avium subspecies. We determined the genetic and phenotypic basis for this difference using sequence analysis and...

  13. Genetic parameters and predicted selection results for maternal traits related to lactation efficiency in sows

    NARCIS (Netherlands)

    Bergsma, R.; Kanis, E.; Verstegen, M.W.A.

    2008-01-01

    The increased productivity of sows increases the risk of a more pronounced negative energy balance during lactation. One possibility to prevent this is to increase the lactation efficiency (LE) genetically and thereby increase milk output for a given feed intake and mobilization of body tissue. The

  14. Prediction of breast cancer risk based on profiling with common genetic variants

    NARCIS (Netherlands)

    N. Mavaddat (Nasim); P.D.P. Pharoah (Paul); K. Michailidou (Kyriaki); J.P. Tyrer (Jonathan); M.N. Brook (Mark N.); M.K. Bolla (Manjeet); Q. Wang (Qing); J. Dennis (Joe); A.M. Dunning (Alison); M. Shah (Mitul); R.N. Luben (Robert); J. Brown (Judith); S.E. Bojesen (Stig); B.G. Nordestgaard (Børge); S.F. Nielsen (Sune F.); H. Flyger (Henrik); K. Czene (Kamila); H. Darabi (Hatef); M. Eriksson (Mikael); J. Peto (Julian); I. dos Santos Silva (Isabel); F. Dudbridge (Frank); N. Johnson (Nichola); M.K. Schmidt (Marjanka); A. Broeks (Annegien); S. Verhoef; E.J. Rutgers (Emiel J.); A.J. Swerdlow (Anthony ); A. Ashworth (Alan); N. Orr (Nick); M. Schoemaker (Minouk); J.D. Figueroa (Jonine); S.J. Chanock (Stephen); L.A. Brinton (Louise); J. Lissowska (Jolanta); F.J. Couch (Fergus); J.E. Olson (Janet); C. Vachon (Celine); V.S. Pankratz (Shane); D. Lambrechts (Diether); H. Wildiers (Hans); C. van Ongeval (Chantal); E. van Limbergen (Erik); V. Kristensen (Vessela); G. Grenaker Alnæs (Grethe); S. Nord (Silje); A.-L. Borresen-Dale (Anne-Lise); H. Nevanlinna (Heli); T.A. Muranen (Taru); K. Aittomäki (Kristiina); C. Blomqvist (Carl); J. Chang-Claude (Jenny); A. Rudolph (Anja); P. Seibold (Petra); D. Flesch-Janys (Dieter); P.A. Fasching (Peter); L. Haeberle (Lothar); A.B. Ekici (Arif); M.W. Beckmann (Matthias); B. Burwinkel (Barbara); F. Marme (Federick); A. Schneeweiss (Andreas); C. Sohn (Christof); A. Trentham-Dietz (Amy); P. Newcomb (Polly); L. Titus (Linda); K.M. Egan (Kathleen M.); D. Hunter (David); S. Lindstrom (Stephen); R. Tamimi (Rulla); P. Kraft (Peter); N. Rahman (Nazneen); C. Turnbull (Clare); A. Renwick (Anthony); S. Seal (Sheila); J. Li (Jingmei); J. Liu (Jianjun); M.K. Humphreys (Manjeet); J. Benítez (Javier); M.P. Zamora (Pilar); J.I. Arias Pérez (José Ignacio); P. Menéndez (Primitiva); A. Jakubowska (Anna); J. Lubinski (Jan); K. Jaworska-Bieniek (Katarzyna); K. Durda (Katarzyna); N.V. Bogdanova (Natalia); N.N. Antonenkova (Natalia); T. Dörk (Thilo); H. Anton-Culver (Hoda); S.L. Neuhausen (Susan); A. Ziogas (Argyrios); L. Bernstein (Leslie); P. Devilee (Peter); R.A.E.M. Tollenaar (Rob); C.M. Seynaeve (Caroline); C.J. van Asperen (Christi); A. Cox (Angela); S.S. Cross (Simon); M.W.R. Reed (Malcolm); E.K. Khusnutdinova (Elza); M. Bermisheva (Marina); D. Prokofyeva (Darya); Z. Takhirova (Zalina); A. Meindl (Alfons); R.K. Schmutzler (Rita); C. Sutter (Christian); R. Yang (Rongxi); P. Schürmann (Peter); M. Bremer (Michael); H. Christiansen (Hans); T.-W. Park-Simon; P. Hillemanns (Peter); P. Guénel (Pascal); T. Truong (Thérèse); F. Menegaux (Florence); M. Sanchez (Marie); P. Radice (Paolo); P. Peterlongo (Paolo); S. Manoukian (Siranoush); V. Pensotti (Valeria); J. Hopper (John); H. Tsimiklis (Helen); C. Apicella (Carmel); M.C. Southey (Melissa); H. Brauch (Hiltrud); T. Brüning (Thomas); Y.-D. Ko (Yon-Dschun); A.J. Sigurdson (Alice); M.M. Doody (Michele M.); U. Hamann (Ute); D. Torres (Diana); H.U. Ulmer (Hans); A. Försti (Asta); E.J. Sawyer (Elinor); I.P. Tomlinson (Ian); M. Kerin (Michael); N. Miller (Nicola); I.L. Andrulis (Irene); J.A. Knight (Julia); G. Glendon (Gord); A. Marie Mulligan (Anna); G. Chenevix-Trench (Georgia); R. Balleine (Rosemary); G.G. Giles (Graham); R.L. Milne (Roger); C.A. McLean (Catriona Ann); A. Lindblom (Annika); S. Margolin (Sara); C.A. Haiman (Christopher); B.E. Henderson (Brian); F. Schumacher (Fredrick); L. Le Marchand (Loic); U. Eilber (Ursula); S. Wang-Gohrke (Shan); M.J. Hooning (Maartje); A. Hollestelle (Antoinette); A.M.W. van den Ouweland (Ans); L.B. Koppert (Lisa); J. Carpenter (Jane); C. Clarke (Christine); R.J. Scott (Rodney J.); A. Mannermaa (Arto); V. Kataja (Vesa); V-M. Kosma (Veli-Matti); J.M. Hartikainen (J.); H. Brenner (Hermann); V. Arndt (Volker); C. Stegmaier (Christa); A. Karina Dieffenbach (Aida); R. Winqvist (Robert); K. Pykäs (Katri); A. Jukkola-Vuorinen (Arja); M. Grip (Mervi); K. Offit (Kenneth); J. Vijai (Joseph); M. Robson (Mark); R. Rau-Murthy (Rohini); M. Dwek (Miriam); R. Swann (Ruth); K. Annie Perkins (Katherine); M.S. Goldberg (Mark); F. Labrèche (France); M. Dumont (Martine); D. Eccles (Diana); W. Tapper (William); M. Rafiq (Meena); E.M. John (Esther M.); A.S. Whittemore (Alice); S. Slager (Susan); D. Yannoukakos (Drakoulis); A.E. Toland (Amanda); S. Yao (Song); W. Zheng (Wei); S.L. Halverson (Sandra L.); A. González-Neira (Anna); G. Pita (Guillermo); M. Rosario Alonso; N. Álvarez (Nuria); D. Herrero (Daniel); D.C. Tessier (Daniel C.); D. Vincent (Daniel); F. Bacot (Francois); C. Luccarini (Craig); C. Baynes (Caroline); S. Ahmed (Shahana); M. Maranian (Melanie); S. Healey (Sue); J. Simard (Jacques); P. Hall (Per); D.F. Easton (Douglas); M. García-Closas (Montserrat)

    2015-01-01

    textabstractBackground: Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is

  15. Genetic variance partitioning and genome-wide prediction with allele dosage information in autotetraploid potato

    Science.gov (United States)

    Potato breeding cycles typically last 6-7 years because of the modest seed multiplication rate and large number of traits required of new varieties. Genomic selection has the potential to increase genetic gain per unit of time, through higher accuracy and/or a shorter cycle. Both possibilities were ...

  16. Predicting the risk of rheumatoid arthritis and its age of onset through modelling genetic risk variants with smoking.

    Directory of Open Access Journals (Sweden)

    Ian C Scott

    Full Text Available The improved characterisation of risk factors for rheumatoid arthritis (RA suggests they could be combined to identify individuals at increased disease risks in whom preventive strategies may be evaluated. We aimed to develop an RA prediction model capable of generating clinically relevant predictive data and to determine if it better predicted younger onset RA (YORA. Our novel modelling approach combined odds ratios for 15 four-digit/10 two-digit HLA-DRB1 alleles, 31 single nucleotide polymorphisms (SNPs and ever-smoking status in males to determine risk using computer simulation and confidence interval based risk categorisation. Only males were evaluated in our models incorporating smoking as ever-smoking is a significant risk factor for RA in men but not women. We developed multiple models to evaluate each risk factor's impact on prediction. Each model's ability to discriminate anti-citrullinated protein antibody (ACPA-positive RA from controls was evaluated in two cohorts: Wellcome Trust Case Control Consortium (WTCCC: 1,516 cases; 1,647 controls; UK RA Genetics Group Consortium (UKRAGG: 2,623 cases; 1,500 controls. HLA and smoking provided strongest prediction with good discrimination evidenced by an HLA-smoking model area under the curve (AUC value of 0.813 in both WTCCC and UKRAGG. SNPs provided minimal prediction (AUC 0.660 WTCCC/0.617 UKRAGG. Whilst high individual risks were identified, with some cases having estimated lifetime risks of 86%, only a minority overall had substantially increased odds for RA. High risks from the HLA model were associated with YORA (P<0.0001; ever-smoking associated with older onset disease. This latter finding suggests smoking's impact on RA risk manifests later in life. Our modelling demonstrates that combining risk factors provides clinically informative RA prediction; additionally HLA and smoking status can be used to predict the risk of younger and older onset RA, respectively.

  17. Developing genetic epidemiological models to predict risk for nasopharyngeal carcinoma in high-risk population of China.

    Directory of Open Access Journals (Sweden)

    Hong-Lian Ruan

    Full Text Available To date, the only established model for assessing risk for nasopharyngeal carcinoma (NPC relies on the sero-status of the Epstein-Barr virus (EBV. By contrast, the risk assessment models proposed here include environmental risk factors, family history of NPC, and information on genetic variants. The models were developed using epidemiological and genetic data from a large case-control study, which included 1,387 subjects with NPC and 1,459 controls of Cantonese origin. The predictive accuracy of the models were then assessed by calculating the area under the receiver-operating characteristic curves (AUC. To compare the discriminatory improvement of models with and without genetic information, we estimated the net reclassification improvement (NRI and integrated discrimination index (IDI. Well-established environmental risk factors for NPC include consumption of salted fish and preserved vegetables and cigarette smoking (in pack years. The environmental model alone shows modest discriminatory ability (AUC = 0.68; 95% CI: 0.66, 0.70, which is only slightly increased by the addition of data on family history of NPC (AUC = 0.70; 95% CI: 0.68, 0.72. With the addition of data on genetic variants, however, our model's discriminatory ability rises to 0.74 (95% CI: 0.72, 0.76. The improvements in NRI and IDI also suggest the potential usefulness of considering genetic variants when screening for NPC in endemic areas. If these findings are confirmed in larger cohort and population-based case-control studies, use of the new models to analyse data from NPC-endemic areas could well lead to earlier detection of NPC.

  18. Prediction of Adult Dyslipidemia Using Genetic and Childhood Clinical Risk Factors: The Cardiovascular Risk in Young Finns Study.

    Science.gov (United States)

    Nuotio, Joel; Pitkänen, Niina; Magnussen, Costan G; Buscot, Marie-Jeanne; Venäläinen, Mikko S; Elo, Laura L; Jokinen, Eero; Laitinen, Tomi; Taittonen, Leena; Hutri-Kähönen, Nina; Lyytikäinen, Leo-Pekka; Lehtimäki, Terho; Viikari, Jorma S; Juonala, Markus; Raitakari, Olli T

    2017-06-01

    Dyslipidemia is a major modifiable risk factor for cardiovascular disease. We examined whether the addition of novel single-nucleotide polymorphisms for blood lipid levels enhances the prediction of adult dyslipidemia in comparison to childhood lipid measures. Two thousand four hundred and twenty-two participants of the Cardiovascular Risk in Young Finns Study who had participated in 2 surveys held during childhood (in 1980 when aged 3-18 years and in 1986) and at least once in a follow-up study in adulthood (2001, 2007, and 2011) were included. We examined whether inclusion of a lipid-specific weighted genetic risk score based on 58 single-nucleotide polymorphisms for low-density lipoprotein cholesterol, 71 single-nucleotide polymorphisms for high-density lipoprotein cholesterol, and 40 single-nucleotide polymorphisms for triglycerides improved the prediction of adult dyslipidemia compared with clinical childhood risk factors. Adjusting for age, sex, body mass index, physical activity, and smoking in childhood, childhood lipid levels, and weighted genetic risk scores were associated with an increased risk of adult dyslipidemia for all lipids. Risk assessment based on 2 childhood lipid measures and the lipid-specific weighted genetic risk scores improved the accuracy of predicting adult dyslipidemia compared with the approach using only childhood lipid measures for low-density lipoprotein cholesterol (area under the receiver-operating characteristic curve 0.806 versus 0.811; P =0.01) and triglycerides (area under the receiver-operating characteristic curve 0.740 versus area under the receiver-operating characteristic curve 0.758; P dyslipidemia in adulthood. © 2017 American Heart Association, Inc.

  19. Network analysis of genomic alteration profiles reveals co-altered functional modules and driver genes for glioblastoma.

    Science.gov (United States)

    Gu, Yunyan; Wang, Hongwei; Qin, Yao; Zhang, Yujing; Zhao, Wenyuan; Qi, Lishuang; Zhang, Yuannv; Wang, Chenguang; Guo, Zheng

    2013-03-01

    The heterogeneity of genetic alterations in human cancer genomes presents a major challenge to advancing our understanding of cancer mechanisms and identifying cancer driver genes. To tackle this heterogeneity problem, many approaches have been proposed to investigate genetic alterations and predict driver genes at the individual pathway level. However, most of these approaches ignore the correlation of alteration events between pathways and miss many genes with rare alterations collectively contributing to carcinogenesis. Here, we devise a network-based approach to capture the cooperative functional modules hidden in genome-wide somatic mutation and copy number alteration profiles of glioblastoma (GBM) from The Cancer Genome Atlas (TCGA), where a module is a set of altered genes with dense interactions in the protein interaction network. We identify 7 pairs of significantly co-altered modules that involve the main pathways known to be altered in GBM (TP53, RB and RTK signaling pathways) and highlight the striking co-occurring alterations among these GBM pathways. By taking into account the non-random correlation of gene alterations, the property of co-alteration could distinguish oncogenic modules that contain driver genes involved in the progression of GBM. The collaboration among cancer pathways suggests that the redundant models and aggravating models could shed new light on the potential mechanisms during carcinogenesis and provide new indications for the design of cancer therapeutic strategies.

  20. Visceral Adiposity Index (VAI) Is Predictive of an Altered Adipokine Profile in Patients with Type 2 Diabetes

    OpenAIRE

    Amato, M.; Pizzolanti, G.; Torregrossa, V.; Misiano, G.; Milano, S.; Giordano, C.

    2014-01-01

    AIMS: Although there is still no clear definition of "adipose tissue dysfunction" or ATD, the identification of a clinical marker of altered fat distribution and function may provide the needed tools for early identification of a condition of cardiometabolic risk. Our aim was to evaluate the correlations among various anthropometric indices [BMI, Waist Circumference (WC), Hip Circumference (HC), Waist/Hip ratio (WHR), Body Adiposity Index (BAI) and Visceral adiposity Index (VAI)] and several ...

  1. Genetic risk score predicting risk of rheumatoid arthritis phenotypes and age of symptom onset.

    Directory of Open Access Journals (Sweden)

    Lori B Chibnik

    Full Text Available Cumulative genetic profiles can help identify individuals at high-risk for developing RA. We examined the impact of 39 validated genetic risk alleles on the risk of RA phenotypes characterized by serologic and erosive status.We evaluated single nucleotide polymorphisms at 31 validated RA risk loci and 8 Human Leukocyte Antigen alleles among 542 Caucasian RA cases and 551 Caucasian controls from Nurses' Health Study and Nurses' Health Study II. We created a weighted genetic risk score (GRS and evaluated it as 7 ordinal groups using logistic regression (adjusting for age and smoking to assess the relationship between GRS group and odds of developing seronegative (RF- and CCP-, seropositive (RF+ or CCP+, erosive, and seropositive, erosive RA phenotypes. In separate case only analyses, we assessed the relationships between GRS and age of symptom onset. In 542 RA cases, 317 (58% were seropositive, 163 (30% had erosions and 105 (19% were seropositive with erosions. Comparing the highest GRS risk group to the median group, we found an OR of 1.2 (95% CI = 0.8-2.1 for seronegative RA, 3.0 (95% CI = 1.9-4.7 for seropositive RA, 3.2 (95% CI = 1.8-5.6 for erosive RA, and 7.6 (95% CI = 3.6-16.3 for seropositive, erosive RA. No significant relationship was seen between GRS and age of onset.Results suggest that seronegative and seropositive/erosive RA have different genetic architecture and support the importance of considering RA phenotypes in RA genetic studies.

  2. AID protein expression in chronic lymphocytic leukemia/small lymphocytic lymphoma is associated with poor prognosis and complex genetic alterations.

    Science.gov (United States)

    Leuenberger, Mona; Frigerio, Simona; Wild, Peter J; Noetzli, Franziska; Korol, Dimitri; Zimmermann, Dieter R; Gengler, Carole; Probst-Hensch, Nicole M; Moch, Holger; Tinguely, Marianne

    2010-02-01

    The biological behavior of chronic lymphocytic leukemia and small lymphocytic lymphoma is unpredictable. Nonetheless, non-mutated IgV(H) gene rearrangement, ATM (11q22-23) and p53 (17p13) deletion are recognized as unfavorable prognosticators in chronic lymphocytic leukemia. The mRNA expression of activation-induced cytidine deaminase (AID), an enzyme indispensable for somatic hypermutation processes, was claimed to be predictive of non-mutated chronic lymphocytic leukemia cells in blood. Here, we evaluated AID protein expression compared with known molecular and immunohistochemical prognostic indicators in 71 chronic lymphocytic leukemia/small lymphocytic lymphoma patients using a tissue microarray approach. We found AID heterogeneously expressed in tumor cells as shown by colocalization analysis for CD5 and CD23. Ki-67 positive paraimmunoblasts of the proliferation centers displayed the highest expression. This observation is reflected by a significant association of AID positivity with a high proliferation rate (P=0.012). ATM deletion was detected in 10% (6/63) of patients and p53 deletion in 19% (13/67) of patients. Moreover, both ATM (P=0.002) and p53 deletion (P=0.004) were significantly associated with AID. IgV(H) gene mutation was seen in 45% (27/60) of patients. Twenty-five percent (17/69) of patients with AID-positive chronic lymphocytic leukemia/small lymphocytic lymphoma displayed a shorter survival than AID-negative chronic lymphocytic leukemia/small lymphocytic lymphoma patients (61 vs 130 months, P=0.001). Although there was a trend, we could not show an association with the IgV(H) gene mutation status. Taken together, our study shows that AID expression is an indicator of an unfavorable prognosis in chronic lymphocytic leukemia/small lymphocytic lymphoma patients, although it is not a surrogate marker for the IgV(H) status. Furthermore, the microenvironment of proliferation centers seems to influence AID regulation and might be an initiating factor

  3. Molecular genetic alterations in egfr CA-SSR-1 microsatellite and egfr copy number changes are associated with aggressiveness in thymoma.

    Science.gov (United States)

    Conti, Salvatore; Gallo, Enzo; Sioletic, Stefano; Facciolo, Francesco; Palmieri, Giovannella; Lauriola, Libero; Evoli, Amelia; Martucci, Robert; Di Benedetto, Anna; Novelli, Flavia; Giannarelli, Diana; Deriu, Gloria; Granone, Pierluigi; Ottaviano, Margaret; Muti, Paola; Pescarmona, Edoardo; Marino, Mirella

    2016-03-01

    The key role of egfr in thymoma pathogenesis has been questioned following the failure in identifying recurrent genetic alterations of egfr coding sequences and relevant egfr amplification rate. We investigated the role of the non-coding egfr CA simple sequence repeat 1 (CA-SSR-1) in a thymoma case series. We used sequencing and egfr-fluorescence in situ hybridization (FISH) to genotype 43 thymomas; (I) for polymorphisms and somatic loss of heterozygosity of the non-coding egfr CA-SSR-1 microsatellite and (II) for egfr gene copy number changes. We found two prevalent CA-SSR-1 genotypes: a homozygous 16 CA repeat and a heterozygous genotype, bearing alleles with 16 and 20 CA repeats. The average combined allele length was correlated with tumor subtype: shorter sequences were significantly associated with the more aggressive WHO thymoma subtype group including B2/B3, B3 and B3/C histotypes. Four out of 29 informative cases analysed for somatic CA-SSR-1 loss of heterozygosity showed allelic imbalance (AI), 3/4 with loss of the longer allele. By egfr-FISH analysis, 9 out of 33 cases were FISH positive. Moreover, the two integrated techniques demonstrated that 3 out of 4 CA-SSR-1-AI positive cases with short allele relative prevalence showed significantly low or high chromosome 7 "polysomy"/increased gene copy number by egfr-FISH. Our molecular and genetic and follow up data indicated that CA-SSR-1-allelic imbalance with short allele relative prevalence significantly correlated with EGFR 3+ immunohistochemical score, increased egfr Gene Copy Number, advanced stage and with relapsing/metastatic behaviour in thymomas.

  4. A Building Model Framework for a Genetic Algorithm Multi-objective Model Predictive Control

    DEFF Research Database (Denmark)

    Arendt, Krzysztof; Ionesi, Ana; Jradi, Muhyiddine

    2016-01-01

    Model Predictive Control (MPC) of building systems is a promising approach to optimize building energy performance. In contrast to traditional control strategies which are reactive in nature, MPC optimizes the utilization of resources based on the predicted effects. It has been shown that energy ...

  5. Comparison of deterministically predicted genetic gains with those realised in a South African Eucalyptus grandis breeding program

    CSIR Research Space (South Africa)

    Verryn, SD

    2009-06-01

    Full Text Available breeding endeavours, are essential for modelling and predicting the economic impact of further genetic improvement. Materials and Methods The “South African Population” (plantation origin) breeding lines with the F1 generation (‘SSO’-series), F2 (‘A... trials SSO1 and SSO4, as representatives of the improvement. It was assumed that selective thinning of the ‘male families’ took place at 50%. (Male families are trees which contribute towards the pollen cloud. These families may be selectively thinned...

  6. Direct-to-consumer advertising of predictive genetic tests: a health belief model based examination of consumer response.

    Science.gov (United States)

    Rollins, Brent L; Ramakrishnan, Shravanan; Perri, Matthew

    2014-01-01

    Direct-to-consumer (DTC) advertising of predictive genetic tests (PGTs) has added a new dimension to health advertising. This study used an online survey based on the health belief model framework to examine and more fully understand consumers' responses and behavioral intentions in response to a PGT DTC advertisement. Overall, consumers reported moderate intentions to talk with their doctor and seek more information about PGTs after advertisement exposure, though consumers did not seem ready to take the advertised test or engage in active information search. Those who perceived greater threat from the disease, however, had significantly greater behavioral intentions and information search behavior.

  7. Clinical worthlessness of genetic prediction of common forms of diabetes mellitus and related chronic complications: A position statement of the Italian Society of Diabetology.

    Science.gov (United States)

    Buzzetti, R; Prudente, S; Copetti, M; Dauriz, M; Zampetti, S; Garofolo, M; Penno, G; Trischitta, V

    2017-02-01

    We are currently facing several attempts aimed at marketing genetic data for predicting multifactorial diseases, among which diabetes mellitus is one of the more prevalent. The present document primarily aims at providing to practicing physicians a summary of available data regarding the role of genetic information in predicting diabetes and its chronic complications. Firstly, general information about characteristics and performance of risk prediction tools will be presented in order to help clinicians to get acquainted with basic methodological information related to the subject at issue. Then, as far as type 1 diabetes is concerned, available data indicate that genetic information and counseling may be useful only in families with many affected individuals. However, since no disease prevention is possible, the utility of predicting this form of diabetes is at question. In the case of type 2 diabetes, available data really question the utility of adding genetic information on top of well performing, easy available and inexpensive non-genetic markers. Finally, the possibility of using the few available genetic data on diabetic complications for improving our ability to predict them will also be presented and discussed. For cardiovascular complication, the addition of genetic information to models based on clinical features does not translate in a substantial improvement in risk discrimination. For all other diabetic complications genetic information are currently very poor and cannot, therefore, be used for improving risk stratification. In all, nowadays the use of genetic testing for predicting diabetes and its chronic complications is definitively of little value in clinical practice. Copyright © 2016 The Italian Society of Diabetology, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition, and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.

  8. Exploring the genetics underlying autoimmune diseases with network analysis and link prediction

    KAUST Repository

    Alanis Lobato, Gregorio; Cannistraci, Carlo; Ravasi, Timothy

    2014-01-01

    Ever since the first Genome Wide Association Study (GWAS) was carried out we have seen an important number of discoveries of biological and clinical relevance. However, there are some scientists that consider that these research outcomes and their utility are far from what was expected from this experimental design. We instead believe that the thousands of genetic variants associated with complex disorders by means of GWASs are an extremely valuable source of information that needs to be mined in a different way. Based on this philosophy, we followed a holistic perspective to analyze GWAS data and explored the structural properties of the network representation of one of these datasets with the aim to advance our understanding of the genetic intricacies underlying autoimmune human diseases. The simplicity, computational efficiency and precision of the tools proposed in this paper represent a new means to address GWAS data and contribute to the better exploitation of these rich sources of information. © 2014 IEEE.

  9. Exploring the genetics underlying autoimmune diseases with network analysis and link prediction

    KAUST Repository

    Alanis Lobato, Gregorio

    2014-02-01

    Ever since the first Genome Wide Association Study (GWAS) was carried out we have seen an important number of discoveries of biological and clinical relevance. However, there are some scientists that consider that these research outcomes and their utility are far from what was expected from this experimental design. We instead believe that the thousands of genetic variants associated with complex disorders by means of GWASs are an extremely valuable source of information that needs to be mined in a different way. Based on this philosophy, we followed a holistic perspective to analyze GWAS data and explored the structural properties of the network representation of one of these datasets with the aim to advance our understanding of the genetic intricacies underlying autoimmune human diseases. The simplicity, computational efficiency and precision of the tools proposed in this paper represent a new means to address GWAS data and contribute to the better exploitation of these rich sources of information. © 2014 IEEE.

  10. Further improvement of genetic and cytogenetic test pattern with increased relevance predicting carcinogenic and pharmacological effects

    Energy Technology Data Exchange (ETDEWEB)

    Siebert, D.

    1982-08-01

    Testing of chemicals for their genetic activity by applying only one method has the disadvantage, that the results are of limited value. However, a combination of several test systems in such a manner that the apparent difference between the results allows additional conclusions about the pharmacokinetic properties of the substances tested, the correlation between molecular mutations and cytogenetic effects and the possible carcinogenic activity. Three nitrofuran derivatives (nitrofurantoin, carofur and FANFT) tested in six different in vitro and in vivo mutagenicity tests partly showed strong genetic activity without metabolic activation and weak cytogenetic effects. However, polycyclic hydrocarbons needed mammalian metabolism to display their mutagenicity: Dimethylbenzoanthracene and benzo(a)pyrene could be activated by liver microsomes and showed also cytogenetic effects, but phenanthrene was only active in the SCE-test. Out of nine heavy metal salts potassium chromate, potassium dichromate, calcium chromate and cis-dichloro diammine-Pt(II) were effective in at least one genetic and one cytogenetic test. The correlation between mutagenic and the known carcinogenic activity of all test substances was good in the case of the hydrocarbons and the nitrofuran derivatives; the heavy metal salts, however, are of low relevance for the carcinogenicity of the metals itself.

  11. Prediction of direct and indirect genetic gains and genotypic correlations in rubber tree progenies

    Directory of Open Access Journals (Sweden)

    Cecília Khusala Verardi

    2011-09-01

    Full Text Available The objective of this work was to estimate the genetic parameters, genotypic and phenotypic correlations, and direct and indirect genetic gains among and within rubber tree (Hevea brasiliensis progenies. The experiment was set up at the Municipality of Jaú, SP, Brazil. A randomized complete block design was used, with 22 treatments (progenies, 6 replicates, and 10 plants per plot at a spacing of 3x3 m. Three‑year‑old progenies were assessed for girth, rubber yield, and bark thickness by direct and indirect gains and genotypic correlations. The number of latex vessel rings showed the best correlations, correlating positively and significantly with girth and bark thickness. Selection gains among progenies were greater than within progeny for all the variables analyzed. Total gains obtained were high, especially for girth increase and rubber yield, which were 93.38 and 105.95%, respectively. Young progeny selection can maximize the expected genetic gains, reducing the rubber tree selection cycle.

  12. Genetic variation in CFH predicts phenytoin-induced maculopapular exanthema in European-descent patients.

    Science.gov (United States)

    McCormack, Mark; Gui, Hongsheng; Ingason, Andrés; Speed, Doug; Wright, Galen E B; Zhang, Eunice J; Secolin, Rodrigo; Yasuda, Clarissa; Kwok, Maxwell; Wolking, Stefan; Becker, Felicitas; Rau, Sarah; Avbersek, Andreja; Heggeli, Kristin; Leu, Costin; Depondt, Chantal; Sills, Graeme J; Marson, Anthony G; Auce, Pauls; Brodie, Martin J; Francis, Ben; Johnson, Michael R; Koeleman, Bobby P C; Striano, Pasquale; Coppola, Antonietta; Zara, Federico; Kunz, Wolfram S; Sander, Josemir W; Lerche, Holger; Klein, Karl Martin; Weckhuysen, Sarah; Krenn, Martin; Gudmundsson, Lárus J; Stefánsson, Kári; Krause, Roland; Shear, Neil; Ross, Colin J D; Delanty, Norman; Pirmohamed, Munir; Carleton, Bruce C; Cendes, Fernando; Lopes-Cendes, Iscia; Liao, Wei-Ping; O'Brien, Terence J; Sisodiya, Sanjay M; Cherny, Stacey; Kwan, Patrick; Baum, Larry; Cavalleri, Gianpiero L

    2018-01-23

    To characterize, among European and Han Chinese populations, the genetic predictors of maculopapular exanthema (MPE), a cutaneous adverse drug reaction common to antiepileptic drugs. We conducted a case-control genome-wide association study of autosomal genotypes, including Class I and II human leukocyte antigen (HLA) alleles, in 323 cases and 1,321 drug-tolerant controls from epilepsy cohorts of northern European and Han Chinese descent. Results from each cohort were meta-analyzed. We report an association between a rare variant in the complement factor H-related 4 ( CFHR4 ) gene and phenytoin-induced MPE in Europeans ( p = 4.5 × 10 -11 ; odds ratio [95% confidence interval] 7 [3.2-16]). This variant is in complete linkage disequilibrium with a missense variant (N1050Y) in the complement factor H ( CFH ) gene. In addition, our results reinforce the association between HLA-A*31:01 and carbamazepine hypersensitivity. We did not identify significant genetic associations with MPE among Han Chinese patients. The identification of genetic predictors of MPE in CFHR4 and CFH, members of the complement factor H-related protein family, suggest a new link between regulation of the complement system alternative pathway and phenytoin-induced hypersensitivity in European-ancestral patients. Copyright © 2017 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.

  13. Prediction of monthly rainfall on homogeneous monsoon regions of India based on large scale circulation patterns using Genetic Programming

    Science.gov (United States)

    Kashid, Satishkumar S.; Maity, Rajib

    2012-08-01

    SummaryPrediction of Indian Summer Monsoon Rainfall (ISMR) is of vital importance for Indian economy, and it has been remained a great challenge for hydro-meteorologists due to inherent complexities in the climatic systems. The Large-scale atmospheric circulation patterns from tropical Pacific Ocean (ENSO) and those from tropical Indian Ocean (EQUINOO) are established to influence the Indian Summer Monsoon Rainfall. The information of these two large scale atmospheric circulation patterns in terms of their indices is used to model the complex relationship between Indian Summer Monsoon Rainfall and the ENSO as well as EQUINOO indices. However, extracting the signal from such large-scale indices for modeling such complex systems is significantly difficult. Rainfall predictions have been done for 'All India' as one unit, as well as for five 'homogeneous monsoon regions of India', defined by Indian Institute of Tropical Meteorology. Recent 'Artificial Intelligence' tool 'Genetic Programming' (GP) has been employed for modeling such problem. The Genetic Programming approach is found to capture the complex relationship between the monthly Indian Summer Monsoon Rainfall and large scale atmospheric circulation pattern indices - ENSO and EQUINOO. Research findings of this study indicate that GP-derived monthly rainfall forecasting models, that use large-scale atmospheric circulation information are successful in prediction of All India Summer Monsoon Rainfall with correlation coefficient as good as 0.866, which may appears attractive for such a complex system. A separate analysis is carried out for All India Summer Monsoon rainfall for India as one unit, and five homogeneous monsoon regions, based on ENSO and EQUINOO indices of months of March, April and May only, performed at end of month of May. In this case, All India Summer Monsoon Rainfall could be predicted with 0.70 as correlation coefficient with somewhat lesser Correlation Coefficient (C.C.) values for different

  14. Common genetic variants in the CLDN2 and PRSS1-PRSS2 loci alter risk for alcohol-related and sporadic pancreatitis

    Science.gov (United States)

    Whitcomb, David C.; LaRusch, Jessica; Krasinskas, Alyssa M.; Klei, Lambertus; Smith, Jill P.; Brand, Randall E.; Neoptolemos, John P.; Lerch, Markus M.; Tector, Matt; Sandhu, Bimaljit S.; Guda, Nalini M.; Orlichenko, Lidiya; Alkaade, Samer; Amann, Stephen T.; Anderson, Michelle A.; Baillie, John; Banks, Peter A.; Conwell, Darwin; Coté, Gregory A.; Cotton, Peter B.; DiSario, James; Farrer, Lindsay A.; Forsmark, Chris E.; Johnstone, Marianne; Gardner, Timothy B.; Gelrud, Andres; Greenhalf, William; Haines, Jonathan L.; Hartman, Douglas J.; Hawes, Robert A.; Lawrence, Christopher; Lewis, Michele; Mayerle, Julia; Mayeux, Richard; Melhem, Nadine M.; Money, Mary E.; Muniraj, Thiruvengadam; Papachristou, Georgios I.; Pericak-Vance, Margaret A.; Romagnuolo, Joseph; Schellenberg, Gerard D.; Sherman, Stuart; Simon, Peter; Singh, Vijay K.; Slivka, Adam; Stolz, Donna; Sutton, Robert; Weiss, Frank Ulrich; Wilcox, C. Mel; Zarnescu, Narcis Octavian; Wisniewski, Stephen R.; O'Connell, Michael R.; Kienholz, Michelle L.; Roeder, Kathryn; Barmada, M. Michael; Yadav, Dhiraj; Devlin, Bernie; Albert, Marilyn S.; Albin, Roger L.; Apostolova, Liana G.; Arnold, Steven E.; Baldwin, Clinton T.; Barber, Robert; Barnes, Lisa L.; Beach, Thomas G.; Beecham, Gary W.; Beekly, Duane; Bennett, David A.; Bigio, Eileen H.; Bird, Thomas D.; Blacker, Deborah; Boxer, Adam; Burke, James R.; Buxbaum, Joseph D.; Cairns, Nigel J.; Cantwell, Laura B.; Cao, Chuanhai; Carney, Regina M.; Carroll, Steven L.; Chui, Helena C.; Clark, David G.; Cribbs, David H.; Crocco, Elizabeth A.; Cruchaga, Carlos; DeCarli, Charles; Demirci, F. Yesim; Dick, Malcolm; Dickson, Dennis W.; Duara, Ranjan; Ertekin-Taner, Nilufer; Faber, Kelley M.; Fallon, Kenneth B.; Farlow, Martin R.; Ferris, Steven; Foroud, Tatiana M.; Frosch, Matthew P.; Galasko, Douglas R.; Ganguli, Mary; Gearing, Marla; Geschwind, Daniel H.; Ghetti, Bernardino; Gilbert, John R.; Gilman, Sid; Glass, Jonathan D.; Goate, Alison M.; Graff-Radford, Neill R.; Green, Robert C.; Growdon, John H.; Hakonarson, Hakon; Hamilton-Nelson, Kara L.; Hamilton, Ronald L.; Harrell, Lindy E.; Head, Elizabeth; Honig, Lawrence S.; Hulette, Christine M.; Hyman, Bradley T.; Jicha, Gregory A.; Jin, Lee-Way; Jun, Gyungah; Kamboh, M. Ilyas; Karydas, Anna; Kaye, Jeffrey A.; Kim, Ronald; Koo, Edward H.; Kowall, Neil W.; Kramer, Joel H.; Kramer, Patricia; Kukull, Walter A.; LaFerla, Frank M.; Lah, James J.; Leverenz, James B.; Levey, Allan I.; Li, Ge; Lin, Chiao-Feng; Lieberman, Andrew P.; Lopez, Oscar L.; Lunetta, Kathryn L.; Lyketsos, Constantine G.; Mack, Wendy J.; Marson, Daniel C.; Martin, Eden R.; Martiniuk, Frank; Mash, Deborah C.; Masliah, Eliezer; McKee, Ann C.; Mesulam, Marsel; Miller, Bruce L.; Miller, Carol A.; Miller, Joshua W.; Montine, Thomas J.; Morris, John C.; Murrell, Jill R.; Naj, Adam C.; Olichney, John M.; Parisi, Joseph E.; Peskind, Elaine; Petersen, Ronald C.; Pierce, Aimee; Poon, Wayne W.; Potter, Huntington; Quinn, Joseph F.; Raj, Ashok; Raskind, Murray; Reiman, Eric M.; Reisberg, Barry; Reitz, Christiane; Ringman, John M.; Roberson, Erik D.; Rosen, Howard J.; Rosenberg, Roger N.; Sano, Mary; Saykin, Andrew J.; Schneider, Julie A.; Schneider, Lon S.; Seeley, William W.; Smith, Amanda G.; Sonnen, Joshua A.; Spina, Salvatore; Stern, Robert A.; Tanzi, Rudolph E.; Trojanowski, John Q.; Troncoso, Juan C.; Tsuang, Debby W.; Valladares, Otto; Van Deerlin, Vivianna M.; Van Eldik, Linda J.; Vardarajan, Badri N.; Vinters, Harry V.; Vonsattel, Jean Paul; Wang, Li-San; Weintraub, Sandra; Welsh-Bohmer, Kathleen A.; Williamson, Jennifer; Woltjer, Randall L.; Wright, Clinton B.; Younkin, Steven G.; Yu, Chang-En; Yu, Lei

    2012-01-01

    Pancreatitis is a complex, progressively destructive inflammatory disorder. Alcohol was long thought to be the primary causative agent, but genetic contributions have been of interest since the discovery that rare PRSS1, CFTR, and SPINK1 variants were associated with pancreatitis risk. We now report two significant genome-wide associations identified and replicated at PRSS1-PRSS2 (1×10-12) and x-linked CLDN2 (p < 1×10-21) through a two-stage genome-wide study (Stage 1, 676 cases and 4507 controls; Stage 2, 910 cases and 4170 controls). The PRSS1 variant affects susceptibility by altering expression of the primary trypsinogen gene. The CLDN2 risk allele is associated with atypical localization of claudin-2 in pancreatic acinar cells. The homozygous (or hemizygous male) CLDN2 genotype confers the greatest risk, and its alleles interact with alcohol consumption to amplify risk. These results could partially explain the high frequency of alcohol-related pancreatitis in men – male hemizygous frequency is 0.26, female homozygote is 0.07. PMID:23143602

  15. Role of laboratory biomarkers in monitoring and prediction of the effectiveness of treatment of rheumatic diseases using genetically engineered drugs

    Directory of Open Access Journals (Sweden)

    Elena Nikolayevna Aleksandrova

    2014-03-01

    Full Text Available Significant progress in treating immunoinflammatory rheumatic diseases (RD is related to the design of a novel family of drugs, genetically engineered (GE drugs. Molecular and cellular biomarkers (antibodies, indicators of acute inflammation, cytokines, chemokines, growth factors, endothelial activation markers, immunoglobulins, cryoglobulins, T- and B-cell subpopulations, products of bone and cartilage metabolism, genetic and metabolic markers that allow one to conduct immunological monitoring and prediction of the effectiveness of RD therapy using tumor necrosis factor α inhibitors (infliximab, adalimumab, golimumab, etanercept, anti-B-cell drugs (rituximab, belimumab, interleukin-6 receptor antagonist (tocilizumab, and T-cell costimulation blocker (abatacept have been detected in blood, synovial fluid, urine, and bioptates of the affected tissues. In addition to the conventional uniplex immunodiagnostics techniques, multiplex analysis of marker, which is based on genetic, transcriptomic and proteomic technologies using DNA and protein microarrays, polymerase chain reaction, and flow cytometry, is becoming increasingly widespread. The search for and validation of immunological predictors of the effective response to GE drug therapy make it possible to optimize and reduce the cost of therapy using these drugs in future.

  16. Role of laboratory biomarkers in monitoring and prediction of the effectiveness of treatment of rheumatic diseases using genetically engineered drugs

    Directory of Open Access Journals (Sweden)

    Elena Nikolayevna Aleksandrova

    2014-01-01

    Full Text Available Significant progress in treating immunoinflammatory rheumatic diseases (RD is related to the design of a novel family of drugs, genetically engineered (GE drugs. Molecular and cellular biomarkers (antibodies, indicators of acute inflammation, cytokines, chemokines, growth factors, endothelial activation markers, immunoglobulins, cryoglobulins, T- and B-cell subpopulations, products of bone and cartilage metabolism, genetic and metabolic markers that allow one to conduct immunological monitoring and prediction of the effectiveness of RD therapy using tumor necrosis factor α inhibitors (infliximab, adalimumab, golimumab, etanercept, anti-B-cell drugs (rituximab, belimumab, interleukin-6 receptor antagonist (tocilizumab, and T-cell costimulation blocker (abatacept have been detected in blood, synovial fluid, urine, and bioptates of the affected tissues. In addition to the conventional uniplex immunodiagnostics techniques, multiplex analysis of marker, which is based on genetic, transcriptomic and proteomic technologies using DNA and protein microarrays, polymerase chain reaction, and flow cytometry, is becoming increasingly widespread. The search for and validation of immunological predictors of the effective response to GE drug therapy make it possible to optimize and reduce the cost of therapy using these drugs in future.

  17. Prediction of China's coal production-environmental pollution based on a hybrid genetic algorithm-system dynamics model

    International Nuclear Information System (INIS)

    Yu Shiwei; Wei Yiming

    2012-01-01

    This paper proposes a hybrid model based on genetic algorithm (GA) and system dynamics (SD) for coal production–environmental pollution load in China. GA has been utilized in the optimization of the parameters of the SD model to reduce implementation subjectivity. The chain of “Economic development–coal demand–coal production–environmental pollution load” of China in 2030 was predicted, and scenarios were analyzed. Results show that: (1) GA performs well in optimizing the parameters of the SD model objectively and in simulating the historical data; (2) The demand for coal energy continuously increases, although the coal intensity has actually decreased because of China's persistent economic development. Furthermore, instead of reaching a turning point by 2030, the environmental pollution load continuously increases each year even under the scenario where coal intensity decreased by 20% and investment in pollution abatement increased by 20%; (3) For abating the amount of “three types of wastes”, reducing the coal intensity is more effective than reducing the polluted production per tonne of coal and increasing investment in pollution control. - Highlights: ► We propos a GA-SD model for China's coal production-pollution prediction. ► Genetic algorithm (GA) can objectively and accurately optimize parameters of system dynamics (SD) model. ► Environmental pollution in China is projected to grow in our scenarios by 2030. ► The mechanism of reducing waste production per tonne of coal mining is more effective than others.

  18. Genetic polymorphisms in 5-Fluorouracil-related enzymes predict pathologic response after neoadjuvant chemoradiation for rectal cancer.

    Science.gov (United States)

    Nelson, Bailey; Carter, Jane V; Eichenberger, Maurice R; Netz, Uri; Galandiuk, Susan

    2016-11-01

    Many patients with rectal cancer undergo preoperative neoadjuvant chemoradiation, with approximately 70% exhibiting pathologic downstaging in response to treatment. Currently, there is no accurate test to predict patients who are likely to be complete responders to therapy. 5-Fluorouracil is used regularly in the neoadjuvant treatment of rectal cancer. Genetic polymorphisms affect the activity of thymidylate synthase, an enzyme involved in 5-Fluorouracil metabolism, which may account for observed differences in response to neoadjuvant treatment between patients. Detection of genetic polymorphisms might identify patients who are likely to have a complete response to neoadjuvant therapy and perhaps allow them to avoid operation. DNA was isolated from whole blood taken from patients with newly diagnosed rectal cancer who received neoadjuvant therapy (n = 50). Response to therapy was calculated with a tumor regression score based on histology from the time of operation. Polymerase chain reaction was performed targeting the promoter region of thymidylate synthase. Polymerase chain reaction products were separated using electrophoresis to determine whether patients were homozygous for a double-tandem repeat (2R), a triple-tandem repeat (3R), or were heterozygous (2R/3R). A single nucleotide polymorphism, 3G or 3C, also may be present in the second repeat unit of the triple-tandem repeat allele. Restriction fragment length polymorphism assays were performed in patients with at least one 3R allele using HaeIII. Patients with at least 1 thymidylate synthase 3G allele were more likely to have a complete or partial pathologic response to 5-Fluorouracil neoadjuvant therapy (odds ratio 10.4; 95% confidence interval, 1.3-81.6; P = .01) than those without at least one 3G allele. Identification of rectal cancer patients with specific genetic polymorphisms in enzymes involved in 5-Fluorouracil metabolism seems to predict the likelihood of complete or partial pathologic response

  19. Artificial neural network analysis based on genetic algorithm to predict the performance characteristics of a cross flow cooling tower

    Science.gov (United States)

    Wu, Jiasheng; Cao, Lin; Zhang, Guoqiang

    2018-02-01

    Cooling tower of air conditioning has been widely used as cooling equipment, and there will be broad application prospect if it can be reversibly used as heat source under heat pump heating operation condition. In view of the complex non-linear relationship of each parameter in the process of heat and mass transfer inside tower, In this paper, the BP neural network model based on genetic algorithm optimization (GABP neural network model) is established for the reverse use of cross flow cooling tower. The model adopts the structure of 6 inputs, 13 hidden nodes and 8 outputs. With this model, the outlet air dry bulb temperature, wet bulb temperature, water temperature, heat, sensible heat ratio and heat absorbing efficiency, Lewis number, a total of 8 the proportion of main performance parameters were predicted. Furthermore, the established network model is used to predict the water temperature and heat absorption of the tower at different inlet temperatures. The mean relative error MRE between BP predicted value and experimental value are 4.47%, 3.63%, 2.38%, 3.71%, 6.35%,3.14%, 13.95% and 6.80% respectively; the mean relative error MRE between GABP predicted value and experimental value are 2.66%, 3.04%, 2.27%, 3.02%, 6.89%, 3.17%, 11.50% and 6.57% respectively. The results show that the prediction results of GABP network model are better than that of BP network model; the simulation results are basically consistent with the actual situation. The GABP network model can well predict the heat and mass transfer performance of the cross flow cooling tower.

  20. Can current moisture responses predict soil CO2 efflux under altered precipitation regimes? A synthesis of manipulation experiments

    Science.gov (United States)

    S. Vicca; M. Bahn; M. Estiarte; E. E. van Loon; R. Vargas; G. Alberti; P. Ambus; M. A. Arain; C. Beier; L. P. Bentley; W. Borken; N. Buchmann; S. L. Collins; G. de Dato; J. S. Dukes; C. Escolar; P. Fay; G. Guidolotti; P. J. Hanson; A. Kahmen; G. Kröel-Dulay; T. Ladreiter-Knauss; K. S. Larsen; E. Lellei-Kovacs; E. Lebrija-Trejos; F. T. Maestre; S. Marhan; M. Marshall; P. Meir; Y. Miao; J. Muhr; P. A. Niklaus; R. Ogaya; J. Peñuelas; C. Poll; L. E. Rustad; K. Savage; A. Schindlbacher; I. K. Schmidt; A. R. Smith; E. D. Sotta; V. Suseela; A. Tietema; N. van Gestel; O. van Straaten; S. Wan; U. Weber; I. A. Janssens

    2014-01-01

    As a key component of the carbon cycle, soil CO2 efflux (SCE) is being increasingly studied to improve our mechanistic understanding of this important carbon flux. Predicting ecosystem responses to climate change often depends an extrapolation of current relationships between ecosystem processes and their climatic drivers to conditions not yet experienced by the...

  1. Can current moisture responses predict soil CO2 efflux under altered precipitation regimes? A synthesis of manipulation experiments

    Science.gov (United States)

    As a key component of the carbon cycle, soil respiration (Rsoil) is being excessively studied with the aim of improving our understanding as well as our ability to predict Rsoil when climate changes. Many manipulation experiments have been performed to test how Rsoil and other carbon fluxes and ecos...

  2. Bias of genetic trend of genomic predictions based on both real dairy cattle and simulated data

    DEFF Research Database (Denmark)

    Ma, Peipei; Lund, Mogens Sandø; Nielsen, Ulrik Sander

    This study investigated the phenomenon of bias in the trend of genomic predictions and attempted to find the reason and solution for this bias. The data used in this study include Danish Jersey data and simulation data. In Jersey data, the bias was reduced when cows were included in the reference...... population. In simulated data, there was no bias when the test animals were unselected cows. When the G matrix was derived from genotypes of causal genes, the bias was reduced. The results suggest that the main reasons for causing the bias of the prediction trends are the selection of bulls and bull dams...

  3. Genetic Factors and Host Traits Predict Spore Morphology for a Butterfly Pathogen

    Directory of Open Access Journals (Sweden)

    Jacobus C. de Roode

    2013-08-01

    Full Text Available Monarch butterflies (Danaus plexippus throughout the world are commonly infected by the specialist pathogen Ophryocystis elektroscirrha (OE. This protozoan is transmitted when larvae ingest infectious stages (spores scattered onto host plant leaves by infected adults. Parasites replicate internally during larval and pupal stages, and adult monarchs emerge covered with millions of dormant spores on the outsides of their bodies. Across multiple monarch populations, OE varies in prevalence and virulence. Here, we examined geographic and genetic variation in OE spore morphology using clonal parasite lineages derived from each of four host populations (eastern and western North America, South Florida and Hawaii. Spores were harvested from experimentally inoculated, captive-reared adult monarchs. Using light microscopy and digital image analysis, we measured the size, shape and color of 30 replicate spores per host. Analyses examined predictors of spore morphology, including parasite source population and clone, parasite load, and the following host traits: family line, sex, wing area, and wing color (orange and black pigmentation. Results showed significant differences in spore size and shape among parasite clones, suggesting genetic determinants of morphological variation. Spore size also increased with monarch wing size, and monarchs with larger and darker orange wings tended to have darker colored spores, consistent with the idea that parasite development depends on variation in host quality and resources. We found no evidence for effects of source population on variation in spore morphology. Collectively, these results provide support for heritable variation in spore morphology and a role for host traits in affecting parasite development.

  4. BAYESIAN PREDICTION OF GENETIC PARAMETERS IN Eucalyptus globulus CLONES UNDER WATER SUPPLY CONDITIONS

    Directory of Open Access Journals (Sweden)

    Freddy Mora

    2013-06-01

    Full Text Available http://dx.doi.org/10.5902/198050989297A Bayesian analysis of genetic parameters for growth traits at twelve months after planting was carried out in twenty nine Eucalyptus globulus clones in southern Chile. Two different environmental conditions were considered: 1 Non-irrigation and; 2 Plants were irrigated with a localized irrigation system. The Bayesian approach was performed using Gibbs sampling algorithm in a clone-environment interaction model. Inheritability values ​​were high in the water supply condition (posterior mode: H2=0.41, 0.36 and 0.39 for height, diameter and sectional area, respectively, while in the environment without irrigation, the inheritabilities were significantly lower, which was confirmed by the Bayesian credible intervals (95% probability. The posterior mode of the genetic correlation between sites was positive and high for all traits (r=0.7, 0.65 and 0.8, for height, diameter and sectional area, respectively and according to the credible interval, it was statistically different from zero, indicating a non-significant interaction.

  5. Visceral adiposity index (VAI is predictive of an altered adipokine profile in patients with type 2 diabetes.

    Directory of Open Access Journals (Sweden)

    Marco C Amato

    Full Text Available AIMS: Although there is still no clear definition of "adipose tissue dysfunction" or ATD, the identification of a clinical marker of altered fat distribution and function may provide the needed tools for early identification of a condition of cardiometabolic risk. Our aim was to evaluate the correlations among various anthropometric indices [BMI, Waist Circumference (WC, Hip Circumference (HC, Waist/Hip ratio (WHR, Body Adiposity Index (BAI and Visceral adiposity Index (VAI] and several adipocytokines [Visfatin, Resistin, Leptin, Soluble leptin receptors (sOB-R, Adiponectin, Ghrelin, Adipsin, PAI-1, vascular endothelial growth factor (VEGF, Hepatocyte growth factor (HGF TNF-α, hs-CRP, IL-6, IL-18] in patients with type 2 diabetes (DM2. MATERIALS AND METHODS: Ninety-one DM2 patients (age: 65.25 ± 6.38 years; 42 men and 49 women in stable treatment for the last six months with metformin in monotherapy (1.5-2 g/day were cross-sectionally studied. Clinical, anthropometric, and metabolic parameters were evaluated. Serum adipocytokine levels were assayed with Luminex based kits. RESULTS: At the Pearson's correlation, among all the indices investigated, VAI showed a significant correlation with almost all adipocytokines analyzed [Visfatin, Resistin and hsCRP (all p<0.001; Adiponectin, sOb-R, IL-6, IL-18, HGF (all p<0.010; Ghrelin and VEGF (both p<0.05]. Through a two-step cluster analysis, 55 patients were identified with the most altered adipocytokine profile (patients with ATD. At a ROC analysis, VAI showed the highest C-statistic [0.767 (95% CI 0.66-0.84] of all the indices. CONCLUSIONS: Our study suggests that the VAI, among the most common indexes of adiposity assessment, shows the best correlation with the best known adipocytokines and cardiometabolic risk serum markers. Although to date we are still far from clearly identifying an ATD, the VAI would be an easy tool for clearly mirroring a condition of cardiometabolic risk, in the absence of an

  6. Sleep apnea predicts distinct alterations in glucose homeostasis and biomarkers in obese adults with normal and impaired glucose metabolism

    Directory of Open Access Journals (Sweden)

    Hill Nathan R

    2010-12-01

    Full Text Available Abstract Background Notwithstanding previous studies supporting independent associations between obstructive sleep apnea (OSA and prevalence of diabetes, the underlying pathogenesis of impaired glucose regulation in OSA remains unclear. We explored mechanisms linking OSA with prediabetes/diabetes and associated biomarker profiles. We hypothesized that OSA is associated with distinct alterations in glucose homeostasis and biomarker profiles in subjects with normal (NGM and impaired glucose metabolism (IGM. Methods Forty-five severely obese adults (36 women without certain comorbidities/medications underwent anthropometric measurements, polysomnography, and blood tests. We measured fasting serum glucose, insulin, selected cytokines, and calculated homeostasis model assessment estimates of insulin sensitivity (HOMA-IS and pancreatic beta-cell function (HOMA-B. Results Both increases in apnea-hypopnea index (AHI and the presence of prediabetes/diabetes were associated with reductions in HOMA-IS in the entire cohort even after adjustment for sex, race, age, and BMI (P = 0.003. In subjects with NGM (n = 30, OSA severity was associated with significantly increased HOMA-B (a trend towards decreased HOMA-IS independent of sex and adiposity. OSA-related oxyhemoglobin desaturations correlated with TNF-α (r=-0.76; P = 0.001 in women with NGM and with IL-6 (rho=-0.55; P = 0.035 in women with IGM (n = 15 matched individually for age, adiposity, and AHI. Conclusions OSA is independently associated with altered glucose homeostasis and increased basal beta-cell function in severely obese adults with NGM. The findings suggest that moderate to severe OSA imposes an excessive functional demand on pancreatic beta-cells, which may lead to their exhaustion and impaired secretory capacity over time. The two distinct biomarker profiles linking sleep apnea with NGM and IGM via TNF-α and IL-6 have been discerned in our study to suggest that sleep apnea and particularly

  7. A Genetic Programming Method for the Identification of Signal Peptides and Prediction of Their Cleavage Sites

    Directory of Open Access Journals (Sweden)

    David Lennartsson

    2004-01-01

    Full Text Available A novel approach to signal peptide identification is presented. We use an evolutionary algorithm for automatic evolution of classification programs, so-called programmatic motifs. The variant of evolutionary algorithm used is called genetic programming where a population of solution candidates in the form of full computer programs is evolved, based on training examples consisting of signal peptide sequences. The method is compared with a previous work using artificial neural network (ANN approaches. Some advantages compared to ANNs are noted. The programmatic motif can perform computational tasks beyond that of feed-forward neural networks and has also other advantages such as readability. The best motif evolved was analyzed and shown to detect the h-region of the signal peptide. A powerful parallel computer cluster was used for the experiment.

  8. Genetic tests for predicting the toxicity and efficacy of anticancer chemotherapy.

    Science.gov (United States)

    Mladosievicova, B; Carter, A; Kristova, V

    2007-01-01

    The standard anticancer therapy based "on one size fits all" modality has been determined to be ineffective or to be the cause of adverse drug reactions in many oncologic patients. Most pharmacogenetic and pharmacogenomic studies so far have been focused on toxicity of anticancer drugs such as 6-mercaptopurine, thioguanine, irinotecan, methotrexate, 5-fluorouracil (5-FU). Variation in genes are known to influence not only toxicity, but also efficacy of chemotherapeutics such as platinum analogues, 5-FU and irinotecan. The majority of current pharmacogenetic studies focus on single enzyme deficiencies as predictors of drug effects; however effects of most anticancer drugs are determined by the interplay of several gene products. These effects are polygenic in nature. This review briefly describes genetic variations that may impact efficacy and toxicity of drugs used in cancer chemotherapy.

  9. Prediction of Layer Thickness in Molten Borax Bath with Genetic Evolutionary Programming

    Science.gov (United States)

    Taylan, Fatih

    2011-04-01

    In this study, the vanadium carbide coating in molten borax bath process is modeled by evolutionary genetic programming (GEP) with bath composition (borax percentage, ferro vanadium (Fe-V) percentage, boric acid percentage), bath temperature, immersion time, and layer thickness data. Five inputs and one output data exist in the model. The percentage of borax, Fe-V, and boric acid, temperature, and immersion time parameters are used as input data and the layer thickness value is used as output data. For selected bath components, immersion time, and temperature variables, the layer thicknesses are derived from the mathematical expression. The results of the mathematical expressions are compared to that of experimental data; it is determined that the derived mathematical expression has an accuracy of 89%.

  10. Prediction model for prevalence and incidence of advanced age-related macular degeneration based on genetic, demographic, and environmental variables.

    Science.gov (United States)

    Seddon, Johanna M; Reynolds, Robyn; Maller, Julian; Fagerness, Jesen A; Daly, Mark J; Rosner, Bernard

    2009-05-01

    The joint effects of genetic, ocular, and environmental variables were evaluated and predictive models for prevalence and incidence of AMD were assessed. Participants in the multicenter Age-Related Eye Disease Study (AREDS) were included in a prospective evaluation of 1446 individuals, of which 279 progressed to advanced AMD (geographic atrophy or neovascular disease) and 1167 did not progress during 6.3 years of follow-up. For prevalent AMD, 509 advanced cases were compared with 222 controls. Covariates for the incidence analysis included age, sex, education, smoking, body mass index (BMI), baseline AMD grade, and the AREDS vitamin-mineral treatment assignment. DNA specimens were evaluated for six variants in five genes related to AMD. Unconditional logistic regression analyses were performed for prevalent and incident advanced AMD. An algorithm was developed and receiver operating characteristic curves and C statistics were calculated to assess the predictive ability of risk scores to discriminate progressors from nonprogressors. All genetic polymorphisms were independently related to prevalence of advanced AMD, controlling for genetic factors, smoking, BMI, and AREDS treatment. Multivariate odds ratios (ORs) were 3.5 (95% confidence interval [CI], 1.7-7.1) for CFH Y402H; 3.7 (95% CI, 1.6-8.4) for CFH rs1410996; 25.4 (95% CI, 8.6-75.1) for LOC387715 A69S (ARMS2); 0.3 (95% CI, 0.1-0.7) for C2 E318D; 0.3 (95% CI, 0.1-0.5) for CFB; and 3.6 (95% CI, 1.4-9.4) for C3 R102G, comparing the homozygous risk/protective genotypes to the referent genotypes. For incident AMD, all these variants except CFB were significantly related to progression to advanced AMD, after controlling for baseline AMD grade and other factors, with ORs from 1.8 to 4.0 for presence of two risk alleles and 0.4 for the protective allele. An interaction was seen between CFH402H and treatment, after controlling for all genotypes. Smoking was independently related to AMD, with a multiplicative joint

  11. Applying Probability Theory for the Quality Assessment of a Wildfire Spread Prediction Framework Based on Genetic Algorithms

    Directory of Open Access Journals (Sweden)

    Andrés Cencerrado

    2013-01-01

    Full Text Available This work presents a framework for assessing how the existing constraints at the time of attending an ongoing forest fire affect simulation results, both in terms of quality (accuracy obtained and the time needed to make a decision. In the wildfire spread simulation and prediction area, it is essential to properly exploit the computational power offered by new computing advances. For this purpose, we rely on a two-stage prediction process to enhance the quality of traditional predictions, taking advantage of parallel computing. This strategy is based on an adjustment stage which is carried out by a well-known evolutionary technique: Genetic Algorithms. The core of this framework is evaluated according to the probability theory principles. Thus, a strong statistical study is presented and oriented towards the characterization of such an adjustment technique in order to help the operation managers deal with the two aspects previously mentioned: time and quality. The experimental work in this paper is based on a region in Spain which is one of the most prone to forest fires: El Cap de Creus.

  12. A genetic variant of the sperm-specific SLO3 K+ channel has altered pH and Ca2+ sensitivities.

    Science.gov (United States)

    Geng, Yanyan; Ferreira, Juan J; Dzikunu, Victor; Butler, Alice; Lybaert, Pascale; Yuan, Peng; Magleby, Karl L; Salkoff, Lawrence; Santi, Celia M

    2017-05-26

    To fertilize an oocyte, sperm must first undergo capacitation in which the sperm plasma membrane becomes hyperpolarized via activation of potassium (K + ) channels and resultant K + efflux. Sperm-specific SLO3 K + channels are responsible for these membrane potential changes critical for fertilization in mouse sperm, and they are only sensitive to pH i However, in human sperm, the major K + conductance is both Ca 2+ - and pH i -sensitive. It has been debated whether Ca 2+ -sensitive SLO1 channels substitute for human SLO3 (hSLO3) in human sperm or whether human SLO3 channels have acquired Ca 2+ sensitivity. Here we show that hSLO3 is rapidly evolving and reveal a natural structural variant with enhanced apparent Ca 2+ and pH sensitivities. This variant allele (C382R) alters an amino acid side chain at a principal interface between the intramembrane-gated pore and the cytoplasmic gating ring of the channel. Because the gating ring contains sensors to intracellular factors such as pH and Ca 2+ , the effectiveness of transduction between the gating ring and the pore domain appears to be enhanced. Our results suggest that sperm-specific genes can evolve rapidly and that natural genetic variation may have led to a SLO3 variant that differs from wild type in both pH and intracellular Ca 2+ sensitivities. Whether this physiological variation confers differences in fertility among males remains to be established. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

  13. Short communication: Genetic lag represents commercial herd genetic merit more accurately than the 4-path selection model.

    Science.gov (United States)

    Dechow, C D; Rogers, G W

    2018-05-01

    Expectation of genetic merit in commercial dairy herds is routinely estimated using a 4-path genetic selection model that was derived for a closed population, but commercial herds using artificial insemination sires are not closed. The 4-path model also predicts a higher rate of genetic progress in elite herds that provide artificial insemination sires than in commercial herds that use such sires, which counters other theoretical assumptions and observations of realized genetic responses. The aim of this work is to clarify whether genetic merit in commercial herds is more accurately reflected under the assumptions of the 4-path genetic response formula or by a genetic lag formula. We demonstrate by tracing the transmission of genetic merit from parents to offspring that the rate of genetic progress in commercial dairy farms is expected to be the same as that in the genetic nucleus. The lag in genetic merit between the nucleus and commercial farms is a function of sire and dam generation interval, the rate of genetic progress in elite artificial insemination herds, and genetic merit of sires and dams. To predict how strategies such as the use of young versus daughter-proven sires, culling heifers following genomic testing, or selective use of sexed semen will alter genetic merit in commercial herds, genetic merit expectations for commercial herds should be modeled using genetic lag expectations. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  14. Journal of Genetics | Indian Academy of Sciences

    Indian Academy of Sciences (India)

    Additionally, the 1/2_g.515G>T variation resulted in a change of amino acid, i.e. glycine to valine. In silico analysis suggests that this change can alter protein structure and function, predicting it to be deleterious or damaging. This work suggests that 1 genetic variants may be important in PD susceptibility in canines.

  15. Prediction of air-to-blood partition coefficients of volatile organic compounds using genetic algorithm and artificial neural network

    International Nuclear Information System (INIS)

    Konoz, Elahe; Golmohammadi, Hassan

    2008-01-01

    An artificial neural network (ANN) was constructed and trained for the prediction of air-to-blood partition coefficients of volatile organic compounds. The inputs of this neural network are theoretically derived descriptors that were chosen by genetic algorithm (GA) and multiple linear regression (MLR) features selection techniques. These descriptors are: R maximal autocorrelation of lag 1 weighted by atomic Sanderson electronegativities (R1E+), electron density on the most negative atom in molecule (EDNA), maximum partial charge for C atom (MXPCC), surface weighted charge partial surface area (WNSA1), fractional charge partial surface area (FNSA2) and atomic charge weighted partial positive surface area (PPSA3). The standard errors of training, test and validation sets for the ANN model are 0.095, 0.148 and 0.120, respectively. Result obtained showed that nonlinear model can simulate the relationship between structural descriptors and the partition coefficients of the molecules in data set accurately

  16. PREDICTIVE CONTROL OF A BATCH POLYMERIZATION SYSTEM USING A FEEDFORWARD NEURAL NETWORK WITH ONLINE ADAPTATION BY GENETIC ALGORITHM

    Directory of Open Access Journals (Sweden)

    A. Cancelier

    Full Text Available Abstract This study used a predictive controller based on an empirical nonlinear model comprising a three-layer feedforward neural network for temperature control of the suspension polymerization process. In addition to the offline training technique, an algorithm was also analyzed for online adaptation of its parameters. For the offline training, the network was statically trained and the genetic algorithm technique was used in combination with the least squares method. For online training, the network was trained on a recurring basis and only the technique of genetic algorithms was used. In this case, only the weights and bias of the output layer neuron were modified, starting from the parameters obtained from the offline training. From the experimental results obtained in a pilot plant, a good performance was observed for the proposed control system, with superior performance for the control algorithm with online adaptation of the model, particularly with respect to the presence of off-set for the case of the fixed parameters model.

  17. Causal Genetic Variation Underlying Metabolome Differences.

    Science.gov (United States)

    Swain-Lenz, Devjanee; Nikolskiy, Igor; Cheng, Jiye; Sudarsanam, Priya; Nayler, Darcy; Staller, Max V; Cohen, Barak A

    2017-08-01

    An ongoing challenge in biology is to predict the phenotypes of individuals from their genotypes. Genetic variants that cause disease often change an individual's total metabolite profile, or metabolome. In light of our extensive knowledge of metabolic pathways, genetic variants that alter the metabolome may help predict novel phenotypes. To link genetic variants to changes in the metabolome, we studied natural variation in the yeast Saccharomyces cerevisiae We used an untargeted mass spectrometry method to identify dozens of metabolite Quantitative Trait Loci (mQTL), genomic regions containing genetic variation that control differences in metabolite levels between individuals. We mapped differences in urea cycle metabolites to genetic variation in specific genes known to regulate amino acid biosynthesis. Our functional assays reveal that genetic variation in two genes, AUA1 and ARG81 , cause the differences in the abundance of several urea cycle metabolites. Based on knowledge of the urea cycle, we predicted and then validated a new phenotype: sensitivity to a particular class of amino acid isomers. Our results are a proof-of-concept that untargeted mass spectrometry can reveal links between natural genetic variants and metabolome diversity. The interpretability of our results demonstrates the promise of using genetic variants underlying natural differences in the metabolome to predict novel phenotypes from genotype. Copyright © 2017 by the Genetics Society of America.

  18. Genetic variants demonstrating flip-flop phenomenon and breast cancer risk prediction among women of African ancestry.

    Science.gov (United States)

    Wang, Shengfeng; Qian, Frank; Zheng, Yonglan; Ogundiran, Temidayo; Ojengbede, Oladosu; Zheng, Wei; Blot, William; Nathanson, Katherine L; Hennis, Anselm; Nemesure, Barbara; Ambs, Stefan; Olopade, Olufunmilayo I; Huo, Dezheng

    2018-04-01

    Few studies have evaluated the performance of existing breast cancer risk prediction models among women of African ancestry. In replication studies of genetic variants, a change in direction of the risk association is a common phenomenon. Termed flip-flop, it means that a variant is risk factor in one population but protective in another, affecting the performance of risk prediction models. We used data from the genome-wide association study (GWAS) of breast cancer in the African diaspora (The Root consortium), which included 3686 participants of African ancestry from Nigeria, USA, and Barbados. Polygenic risk scores (PRSs) were constructed from the published odds ratios (ORs) of four sets of susceptibility loci for breast cancer. Discrimination capacity was measured using the area under the receiver operating characteristic curve (AUC). Flip-flop phenomenon was observed among 30~40% of variants across studies. Using the 34 variants with consistent directionality among previous studies, we constructed a PRS with AUC of 0.531 (95% confidence interval [CI]: 0.512-0.550), which is similar to the PRS using 93 variants and ORs from European ancestry populations (AUC = 0.525, 95% CI: 0.506-0.544). Additionally, we found the 34-variant PRS has good discriminative accuracy in women with family history of breast cancer (AUC = 0.586, 95% CI: 0.532-0.640). We found that PRS based on variants identified from prior GWASs conducted in women of European and Asian ancestries did not provide a comparable degree of risk stratification for women of African ancestry. Further large-scale fine-mapping studies in African ancestry populations are desirable to discover population-specific genetic risk variants.

  19. Feasibility of an Assessment Tool for Children's Competence to Consent to Predictive Genetic Testing: a Pilot Study.

    Science.gov (United States)

    Hein, Irma M; Troost, Pieter W; Lindeboom, Robert; Christiaans, Imke; Grisso, Thomas; van Goudoever, Johannes B; Lindauer, Ramón J L

    2015-12-01

    Knowledge on children's capacities to consent to medical treatment is limited. Also, age limits for asking children's consent vary considerably between countries. Decision-making on predictive genetic testing (PGT) is especially complicated, considering the ongoing ethical debate. In order to examine just age limits for alleged competence to consent in children, we evaluated feasibility of a standardized assessment tool, and investigated cutoff ages for children's competence to consent to PGT. We performed a pilot study, including 17 pediatric outpatients between 6 and 18 years at risk for an autosomal dominantly inherited cardiac disease, eligible for predictive genetic testing. The reference standard for competence was established by experts trained in the relevant criteria for competent decision-making. The MacArthur Competence Assessment Tool for Treatment (MacCAT-T) served as index test. Data analysis included raw agreement between competence classifications, difference in mean ages between children judged competent and judged incompetent, and estimation of cutoff ages for judgments of competence. Twelve (71 %) children were considered competent by the reference standard, and 16 (94 %) by the MacCAT-T, with an overall agreement of 76 %. The expert judgments disagreed in most cases, while the MacCAT-T judgments agreed in 65 %. Mean age of children judged incompetent was 9.3 years and of children judged competent 12.1 years (p = .035). With 90 % sensitivity, children younger than 10.0 years were judged incompetent, with 90 % specificity children older than 11.8 years were judged competent. Feasibility of the MacCAT-T in children is confirmed. Initial findings on age cutoffs are indicative for children between the age of 12 and 18 to be judged competent for involvement in the informed consent process. Future research on appropriate age-limits for children's alleged competence to consent is needed.

  20. Predictive Factors for BRCA1 and BRCA2 Genetic Testing in an Asian Clinic-Based Population.

    Directory of Open Access Journals (Sweden)

    Edward S Y Wong

    Full Text Available The National Comprehensive Cancer Network (NCCN has proposed guidelines for the genetic testing of the BRCA1 and BRCA2 genes, based on studies in western populations. This current study assessed potential predictive factors for BRCA mutation probability, in an Asian population.A total of 359 breast cancer patients, who presented with either a family history (FH of breast and/or ovarian cancer or early onset breast cancer, were accrued at the National Cancer Center Singapore (NCCS. The relationships between clinico-pathological features and mutational status were calculated using the Chi-squared test and binary logistic regression analysis.Of 359 patients, 45 (12.5% had deleterious or damaging missense mutations in BRCA1 and/or BRCA2. BRCA1 mutations were more likely to be found in ER-negative than ER-positive breast cancer patients (P=0.01. Moreover, ER-negative patients with BRCA mutations were diagnosed at an earlier age (40 vs. 48 years, P=0.008. Similarly, triple-negative breast cancer (TNBC patients were more likely to have BRCA1 mutations (P=0.001 and that these patients were diagnosed at a relatively younger age than non-TNBC patients (38 vs. 46 years, P=0.028. Our analysis has confirmed that ER-negative status, TNBC status and a FH of hereditary breast and ovarian cancer (HBOC are strong factors predicting the likelihood of having BRCA mutations.Our study provides evidence that TNBC or ER-negative patients may benefit from BRCA genetic testing, particularly younger patients (<40 years or those with a strong FH of HBOC, in Asian patients.

  1. Parkinsonian motor impairment predicts personality domains related to genetic risk and treatment outcomes in schizophrenia.

    Science.gov (United States)

    Molina, Juan L; Calvó, María; Padilla, Eduardo; Balda, Mara; Alemán, Gabriela González; Florenzano, Néstor V; Guerrero, Gonzalo; Kamis, Danielle; Rangeon, Beatriz Molina; Bourdieu, Mercedes; Strejilevich, Sergio A; Conesa, Horacio A; Escobar, Javier I; Zwir, Igor; Cloninger, C Robert; de Erausquin, Gabriel A

    2017-01-01

    Identifying endophenotypes of schizophrenia is of critical importance and has profound implications on clinical practice. Here we propose an innovative approach to clarify the mechanims through which temperament and character deviance relates to risk for schizophrenia and predict long-term treatment outcomes. We recruited 61 antipsychotic naïve subjects with chronic schizophrenia, 99 unaffected relatives, and 68 healthy controls from rural communities in the Central Andes. Diagnosis was ascertained with the Schedules of Clinical Assessment in Neuropsychiatry; parkinsonian motor impairment was measured with the Unified Parkinson's Disease Rating Scale; mesencephalic parenchyma was evaluated with transcranial ultrasound; and personality traits were assessed using the Temperament and Character Inventory. Ten-year outcome data was available for ~40% of the index cases. Patients with schizophrenia had higher harm avoidance and self-transcendence (ST), and lower reward dependence (RD), cooperativeness (CO), and self-directedness (SD). Unaffected relatives had higher ST and lower CO and SD. Parkinsonism reliably predicted RD, CO, and SD after correcting for age and sex. The average duration of untreated psychosis (DUP) was over 5 years. Further, SD was anticorrelated with DUP and antipsychotic dosing at follow-up. Baseline DUP was related to antipsychotic dose-years. Further, 'explosive/borderline', 'methodical/obsessive', and 'disorganized/schizotypal' personality profiles were associated with increased risk of schizophrenia. Parkinsonism predicts core personality features and treatment outcomes in schizophrenia. Our study suggests that RD, CO, and SD are endophenotypes of the disease that may, in part, be mediated by dopaminergic function. Further, SD is an important determinant of treatment course and outcome.

  2. Feature selection for disruption prediction from scratch in JET by using genetic algorithms and probabilistic predictors

    Energy Technology Data Exchange (ETDEWEB)

    Pereira, Augusto, E-mail: augusto.pereira@ciemat.es [Laboratorio Nacional de Fusión, CIEMAT, Madrid (Spain); Vega, Jesús; Moreno, Raúl [Laboratorio Nacional de Fusión, CIEMAT, Madrid (Spain); Dormido-Canto, Sebastián [Dpto. Informática y Automática – UNED, Madrid (Spain); Rattá, Giuseppe A. [Laboratorio Nacional de Fusión, CIEMAT, Madrid (Spain); Pavón, Fernando [Dpto. Informática y Automática – UNED, Madrid (Spain)

    2015-10-15

    Recently, a probabilistic classifier has been developed at JET to be used as predictor from scratch. It has been applied to a database of 1237 JET ITER-like wall (ILW) discharges (of which 201 disrupted) with good results: success rate of 94% and false alarm rate of 4.21%. A combinatorial analysis between 14 features to ensure the selection of the best ones to achieve good enough results in terms of success rate and false alarm rate was performed. All possible combinations with a number of features between 2 and 7 were tested and 9893 different predictors were analyzed. An important drawback in this analysis was the time required to compute the results that can be estimated in 1731 h (∼2.4 months). Genetic algorithms (GA) are searching algorithms that simulate the process of natural selection. In this article, the GA and the Venn predictors are combined with the objective not only of finding good enough features within the 14 available ones but also of reducing the computational time requirements. Five different performance metrics as measures of the GA fitness function have been evaluated. The best metric was the measurement called Informedness, with just 6 generations (168 predictors at 29.4 h).

  3. ANFIS-based genetic algorithm for predicting the optimal sizing coefficient of photovoltaic supply systems

    Energy Technology Data Exchange (ETDEWEB)

    Mellit, A. [Medea Univ., Medea (Algeria). Inst. of Science Engineering, Dept. of Electronics

    2007-07-01

    Stand-alone photovoltaic (PV) power supply systems are regarded as reliable and economical sources of electricity in rural remote areas, particularly in developing countries. However, the sizing of stand-alone photovoltaic (PV) systems is an important part of the system design. Choosing the optimal number of solar cell panels and the size of the storage battery to be used for a certain application at a particular site is an important economical problem. In this paper, a genetic algorithm (GA) and an adaptive neuro-fuzzy inference scheme (ANFIS) were proposed as a means for determining the optimal size of PV system, particularly, in isolated areas. The GA-ANFIS model was shown to be suitable for modelling the optimal sizing parameters of PVS systems. The GA was used to determine the PV-array capacity and the storage capacity for 60 sites. From this database, 56 pairs relative to 56 sites were used for training the network. Four pairs were used for testing and validating the ANFIS model. A correlation of 99 per cent was achieved when complete unknown data parameters were presented to the model. The proposed technique provided more accurate results than the alternative artificial neural network (ANN) with GA. The advantage of this model was that it could estimate the PV-array area and the useful capacity of the battery from only geographical coordinates. Although the technique was applied and tested in Algeria, it can be generalized for any location in the world. 15 refs., 4 tabs., 8 figs.

  4. Prediction and optimization of fuel cell performance using a multi-objective genetic algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Marques Hobold, Gustavo [Laboratory of Energy Conversion Engineering and Technology, Federal University of Santa Catarina (Brazil); Washington University in St. Louis, MO 63130 (United States); Agarwal, Ramesh K. [Department of Mechanical Engineering and Materials Science, Washington University in St. Louis, MO 63130 (United States)

    2013-07-01

    The attention that is currently being given to the emission of pollutant gases in the atmosphere has made the fuel cell (FC), an energy conversion device that cleanly converts chemical energy into electrical energy, a good alternative to other technologies that still use carbon-based fuels. The temperature plays an important role on the efficiency of an FC as it influences directly the humidity of the membrane, the reversible thermodynamic potential and the partial pressure of water; therefore the thermal control of the fuel cell is the focus of this paper. We present models for both high and low temperature fuel cells based on the solid-oxide fuel cell (SOFC) and the polymer electrolyte membrane fuel cell (PEMFC). A thermodynamic analysis is performed on the cells and the methods of controlling their temperature are discussed. The cell parameters are optimized for both high and low temperatures using a Java-based multi-objective genetic algorithm, which makes use of the logic of the biological theory of evolution to classify individual parameters based on a fitness function in order to maximize the power of the fuel cell. Applications to high and low temperature fuel cells are discussed.

  5. Feature selection for disruption prediction from scratch in JET by using genetic algorithms and probabilistic predictors

    International Nuclear Information System (INIS)

    Pereira, Augusto; Vega, Jesús; Moreno, Raúl; Dormido-Canto, Sebastián; Rattá, Giuseppe A.; Pavón, Fernando

    2015-01-01

    Recently, a probabilistic classifier has been developed at JET to be used as predictor from scratch. It has been applied to a database of 1237 JET ITER-like wall (ILW) discharges (of which 201 disrupted) with good results: success rate of 94% and false alarm rate of 4.21%. A combinatorial analysis between 14 features to ensure the selection of the best ones to achieve good enough results in terms of success rate and false alarm rate was performed. All possible combinations with a number of features between 2 and 7 were tested and 9893 different predictors were analyzed. An important drawback in this analysis was the time required to compute the results that can be estimated in 1731 h (∼2.4 months). Genetic algorithms (GA) are searching algorithms that simulate the process of natural selection. In this article, the GA and the Venn predictors are combined with the objective not only of finding good enough features within the 14 available ones but also of reducing the computational time requirements. Five different performance metrics as measures of the GA fitness function have been evaluated. The best metric was the measurement called Informedness, with just 6 generations (168 predictors at 29.4 h).

  6. Prediction of genetic gains by selection indices using mixed models in elephant grass for energy purposes.

    Science.gov (United States)

    Silva, V B; Daher, R F; Araújo, M S B; Souza, Y P; Cassaro, S; Menezes, B R S; Gravina, L M; Novo, A A C; Tardin, F D; Júnior, A T Amaral

    2017-09-27

    Genetically improved cultivars of elephant grass need to be adapted to different ecosystems with a faster growth speed and lower seasonality of biomass production over the year. This study aimed to use selection indices using mixed models (REML/BLUP) for selecting families and progenies within full-sib families of elephant grass (Pennisetum purpureum) for biomass production. One hundred and twenty full-sib progenies were assessed from 2014 to 2015 in a randomized block design with three replications. During this period, the traits dry matter production, the number of tillers, plant height, stem diameter, and neutral detergent fiber were assessed. Families 3 and 1 were the best classified, being the most indicated for selection effect. Progenies 40, 45, 46, and 49 got the first positions in the three indices assessed in the first cut. The gain for individual 40 was 161.76% using Mulamba and Mock index. The use of selection indices using mixed models is advantageous in elephant grass since they provide high gains with the selection, which are distributed among all the assessed traits in the most appropriate situation to breeding programs.

  7. A non-parametric mixture model for genome-enabled prediction of genetic value for a quantitative trait.

    Science.gov (United States)

    Gianola, Daniel; Wu, Xiao-Lin; Manfredi, Eduardo; Simianer, Henner

    2010-10-01

    A Bayesian nonparametric form of regression based on Dirichlet process priors is adapted to the analysis of quantitative traits possibly affected by cryptic forms of gene action, and to the context of SNP-assisted genomic selection, where the main objective is to predict a genomic signal on phenotype. The procedure clusters unknown genotypes into groups with distinct genetic values, but in a setting in which the number of clusters is unknown a priori, so that standard methods for finite mixture analysis do not work. The central assumption is that genetic effects follow an unknown distribution with some "baseline" family, which is a normal process in the cases considered here. A Bayesian analysis based on the Gibbs sampler produces estimates of the number of clusters, posterior means of genetic effects, a measure of credibility in the baseline distribution, as well as estimates of parameters of the latter. The procedure is illustrated with a simulation representing two populations. In the first one, there are 3 unknown QTL, with additive, dominance and epistatic effects; in the second, there are 10 QTL with additive, dominance and additive × additive epistatic effects. In the two populations, baseline parameters are inferred correctly. The Dirichlet process model infers the number of unique genetic values correctly in the first population, but it produces an understatement in the second one; here, the true number of clusters is over 900, and the model gives a posterior mean estimate of about 140, probably because more replication of genotypes is needed for correct inference. The impact on inferences of the prior distribution of a key parameter (M), and of the extent of replication, was examined via an analysis of mean body weight in 192 paternal half-sib families of broiler chickens, where each sire was genotyped for nearly 7,000 SNPs. In this small sample, it was found that inference about the number of clusters was affected by the prior distribution of M. For a

  8. Genetic polymorphism of human cytochrome P-450 (S)-mephenytoin 4-hydroxylase. Studies with human autoantibodies suggest a functionally altered cytochrome P-450 isozyme as cause of the genetic deficiency

    International Nuclear Information System (INIS)

    Meier, U.T.; Meyer, U.A.

    1987-01-01

    The metabolism of the anticonvulsant mephenytoin is subject to a genetic polymorphism. In 2-5% of Caucasians and 18-23% of Japanese subjects a specific cytochrome P-450 isozyme, P-450 meph, is functionally deficient or missing. The authors have accumulated evidence that autoimmune antibodies observed in sera of patients with tienilic acid induced hepatitis (anti-liver kidney microsome 2 or anti-LKM2 antibodies) specifically recognize the cytochrome P-450 involved in the mephrenytoin hydroxylation polymorphism. This is demonstrated by immunoinhibition and immunoprecipitation of microsomal (S)-mephenytoin 4-hydroxylation activity and by the recognition by anti-LKM2 antibodies of a single [ 125 I]-protein band on immunoblots of human liver microsomes after sodium dodecyl sulfate-polyacrylamide gel electrophoresis or isoelectric focusing. The cytochrome P-450 recognized by anti-LKM2 antibodies was immunopurified from microsomes derived from livers of extensive (EM) or poor metabolizers (PM) of (S)-mephenytoin. Comparison of the EM-type cytochrome P-450 to that isolated from PM livers revealed no difference in regard to immuno-cross-reactivity, molecular weight, isoelectric point, relative content in microsomes, two-dimensional tryptic peptide maps, one-dimensional peptide maps with three proteases, amino acid composition, and amino-terminal protein sequence. Finally, the same protein was precipitated from microsomes prepared from the liver biopsy of a subject phenotyped in vivo as a poor metabolizer of mephenytoin. These data strongly suggest that the mephenytoin hydroxylation deficiency is caused by a minor structural change leading to a functionally altered cytochrome P-450 isozyme

  9. Predictive models for mutations in mismatch repair genes: implication for genetic counseling in developing countries

    Directory of Open Access Journals (Sweden)

    Monteiro Santos Erika

    2012-02-01

    Full Text Available Abstract Background Lynch syndrome (LS is the most common form of inherited predisposition to colorectal cancer (CRC, accounting for 2-5% of all CRC. LS is an autosomal dominant disease characterized by mutations in the mismatch repair genes mutL homolog 1 (MLH1, mutS homolog 2 (MSH2, postmeiotic segregation increased 1 (PMS1, post-meiotic segregation increased 2 (PMS2 and mutS homolog 6 (MSH6. Mutation risk prediction models can be incorporated into clinical practice, facilitating the decision-making process and identifying individuals for molecular investigation. This is extremely important in countries with limited economic resources. This study aims to evaluate sensitivity and specificity of five predictive models for germline mutations in repair genes in a sample of individuals with suspected Lynch syndrome. Methods Blood samples from 88 patients were analyzed through sequencing MLH1, MSH2 and MSH6 genes. The probability of detecting a mutation was calculated using the PREMM, Barnetson, MMRpro, Wijnen and Myriad models. To evaluate the sensitivity and specificity of the models, receiver operating characteristic curves were constructed. Results Of the 88 patients included in this analysis, 31 mutations were identified: 16 were found in the MSH2 gene, 15 in the MLH1 gene and no pathogenic mutations were identified in the MSH6 gene. It was observed that the AUC for the PREMM (0.846, Barnetson (0.850, MMRpro (0.821 and Wijnen (0.807 models did not present significant statistical difference. The Myriad model presented lower AUC (0.704 than the four other models evaluated. Considering thresholds of ≥ 5%, the models sensitivity varied between 1 (Myriad and 0.87 (Wijnen and specificity ranged from 0 (Myriad to 0.38 (Barnetson. Conclusions The Barnetson, PREMM, MMRpro and Wijnen models present similar AUC. The AUC of the Myriad model is statistically inferior to the four other models.

  10. Predictive models for mutations in mismatch repair genes: implication for genetic counseling in developing countries

    Energy Technology Data Exchange (ETDEWEB)

    Monteiro Santos, Erika Maria [Graduation Program, AC Camargo Hospital, Sao Paulo (Brazil); International Center of Research and Training (CIPE), AC Camargo Hospital, Sao Paulo (Brazil); Silva Junior, Wilson Araujo da [Sao Paulo University, Department of Genetics, Medical School of Ribeirao Preto, Ribeirao Preto (Brazil); Carraro, Dirce Maria [Graduation Program, AC Camargo Hospital, Sao Paulo (Brazil); International Center of Research and Training (CIPE), AC Camargo Hospital, Sao Paulo (Brazil); Rossi, Benedito Mauro; Valentin, Mev Dominguez [Graduation Program, AC Camargo Hospital, Sao Paulo (Brazil); Carneiro, Felipe [Graduation Program, AC Camargo Hospital, Sao Paulo (Brazil); International Center of Research and Training (CIPE), AC Camargo Hospital, Sao Paulo (Brazil); Oliveira, Ligia Petrolini de [Graduation Program, AC Camargo Hospital, Sao Paulo (Brazil); Oliveira Ferreira, Fabio de; Junior, Samuel Aguiar [Graduation Program, AC Camargo Hospital, Sao Paulo (Brazil); Hereditary Colorectal Cancer Registry, AC Camargo Hospital, Sao Paulo (Brazil); Nakagawa, Wilson Toshihiko [Hereditary Colorectal Cancer Registry, AC Camargo Hospital, Sao Paulo (Brazil); Gomy, Israel [Graduation Program, AC Camargo Hospital, Sao Paulo (Brazil); Sao Paulo University, Department of Genetics, Medical School of Ribeirao Preto, Ribeirao Preto (Brazil); Faria Ferraz, Victor Evangelista de [Sao Paulo University, Department of Genetics, Medical School of Ribeirao Preto, Ribeirao Preto (Brazil)

    2012-02-09

    Lynch syndrome (LS) is the most common form of inherited predisposition to colorectal cancer (CRC), accounting for 2-5% of all CRC. LS is an autosomal dominant disease characterized by mutations in the mismatch repair genes mutL homolog 1 (MLH1), mutS homolog 2 (MSH2), postmeiotic segregation increased 1 (PMS1), post-meiotic segregation increased 2 (PMS2) and mutS homolog 6 (MSH6). Mutation risk prediction models can be incorporated into clinical practice, facilitating the decision-making process and identifying individuals for molecular investigation. This is extremely important in countries with limited economic resources. This study aims to evaluate sensitivity and specificity of five predictive models for germline mutations in repair genes in a sample of individuals with suspected Lynch syndrome. Blood samples from 88 patients were analyzed through sequencing MLH1, MSH2 and MSH6 genes. The probability of detecting a mutation was calculated using the PREMM, Barnetson, MMRpro, Wijnen and Myriad models. To evaluate the sensitivity and specificity of the models, receiver operating chara