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

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.

Genetic alterations and epigenetic changes in hepatocarcinogenesis

Directory of Open Access Journals (Sweden)

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

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.

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

Science.gov (United States)

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.

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.

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)

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).

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

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.

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.

Does genetic diversity predict health in humans?

Directory of Open Access Journals (Sweden)

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.

Genetic prediction of male pattern baldness.

Directory of Open Access Journals (Sweden)

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.

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...

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

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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.

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.

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.

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.

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

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.

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.

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.

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...

Amygdala functional connectivity, HPA axis genetic variation, and life stress in children and relations to anxiety and emotion regulation

Science.gov (United States)

Pagliaccio, David; Luby, Joan L.; Bogdan, Ryan; Agrawal, Arpana; Gaffrey, Michael S.; Belden, Andrew C.; Botteron, Kelly N.; Harms, Michael P.; Barch, Deanna M.

2015-01-01

Internalizing pathology is related to alterations in amygdala resting state functional connectivity, potentially implicating altered emotional reactivity and/or emotion regulation in the etiological pathway. Importantly, there is accumulating evidence that stress exposure and genetic vulnerability impact amygdala structure/function and risk for internalizing pathology. The present study examined whether early life stress and genetic profile scores (10 single nucleotide polymorphisms within four hypothalamic-pituitary-adrenal axis genes: CRHR1, NR3C2, NR3C1, and FKBP5) predicted individual differences in amygdala functional connectivity in school-age children (9–14 year olds; N=120). Whole-brain regression analyses indicated that increasing genetic ‘risk’ predicted alterations in amygdala connectivity to the caudate and postcentral gyrus. Experience of more stressful and traumatic life events predicted weakened amygdala-anterior cingulate cortex connectivity. Genetic ‘risk’ and stress exposure interacted to predict weakened connectivity between the amygdala and the inferior and middle frontal gyri, caudate, and parahippocampal gyrus in those children with the greatest genetic and environmental risk load. Furthermore, amygdala connectivity longitudinally predicted anxiety symptoms and emotion regulation skills at a later follow-up. Amygdala connectivity mediated effects of life stress on anxiety and of genetic variants on emotion regulation. The current results suggest that considering the unique and interacting effects of biological vulnerability and environmental risk factors may be key to understanding the development of altered amygdala functional connectivity, a potential factor in the risk trajectory for internalizing pathology. PMID:26595470

Amygdala functional connectivity, HPA axis genetic variation, and life stress in children and relations to anxiety and emotion regulation.

Science.gov (United States)

Pagliaccio, David; Luby, Joan L; Bogdan, Ryan; Agrawal, Arpana; Gaffrey, Michael S; Belden, Andrew C; Botteron, Kelly N; Harms, Michael P; Barch, Deanna M

2015-11-01

Internalizing pathology is related to alterations in amygdala resting state functional connectivity, potentially implicating altered emotional reactivity and/or emotion regulation in the etiological pathway. Importantly, there is accumulating evidence that stress exposure and genetic vulnerability impact amygdala structure/function and risk for internalizing pathology. The present study examined whether early life stress and genetic profile scores (10 single nucleotide polymorphisms within 4 hypothalamic-pituitary-adrenal axis genes: CRHR1, NR3C2, NR3C1, and FKBP5) predicted individual differences in amygdala functional connectivity in school-age children (9- to 14-year-olds; N = 120). Whole-brain regression analyses indicated that increasing genetic "risk" predicted alterations in amygdala connectivity to the caudate and postcentral gyrus. Experience of more stressful and traumatic life events predicted weakened amygdala-anterior cingulate cortex connectivity. Genetic "risk" and stress exposure interacted to predict weakened connectivity between the amygdala and the inferior and middle frontal gyri, caudate, and parahippocampal gyrus in those children with the greatest genetic and environmental risk load. Furthermore, amygdala connectivity longitudinally predicted anxiety symptoms and emotion regulation skills at a later follow-up. Amygdala connectivity mediated effects of life stress on anxiety and of genetic variants on emotion regulation. The current results suggest that considering the unique and interacting effects of biological vulnerability and environmental risk factors may be key to understanding the development of altered amygdala functional connectivity, a potential factor in the risk trajectory for internalizing pathology. (c) 2015 APA, all rights reserved).

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...

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...

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.

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...

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.

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.

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...

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

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.

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.

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.

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.

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.

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.

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.

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.

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...

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.

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.

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

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.

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...

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.

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.

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.

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

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

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

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.

Hypergravity-induced altered behavior in Drosophila

Science.gov (United States)

Hosamani, Ravikumar; Wan, Judy; Marcu, Oana; Bhattacharya, Sharmila

2012-07-01

Microgravity and mechanical stress are important factors of the spaceflight environment, and affect astronaut health and behavior. Structural, functional, and behavioral mechanisms of all cells and organisms are adapted to Earth's gravitational force, 1G, while altered gravity can pose challenges to their adaptability to this new environment. On ground, hypergravity paradigms have been used to predict and complement studies on microgravity. Even small changes that take place at a molecular and genetic level during altered gravity may result in changes in phenotypic behavior. Drosophila provides a robust and simple, yet very reliable model system to understand the complexity of hypergravity-induced altered behavior, due to availability of a plethora of genetic tools. Locomotor behavior is a sensitive parameter that reflects the array of molecular adaptive mechanisms recruited during exposure to altered gravity. Thus, understanding the genetic basis of this behavior in a hypergravity environment could potentially extend our understanding of mechanisms of adaptation in microgravity. In our laboratory we are trying to dissect out the cellular and molecular mechanisms underlying hypergravity-induced oxidative stress, and its potential consequences on behavioral alterations by using Drosophila as a model system. In the present study, we employed pan-neuronal and mushroom body specific knock-down adult flies by using Gal4/UAS system to express inverted repeat transgenes (RNAi) to monitor and quantify the hypergravity-induced behavior in Drosophila. We established that acute hypergravity (3G for 60 min) causes a significant and robust decrease in the locomotor behavior in adult Drosophila, and that this change is dependent on genes related to Parkinson's disease, such as DJ-1α , DJ-1β , and parkin. In addition, we also showed that anatomically the control of this behavior is significantly processed in the mushroom body region of the fly brain. This work links a molecular

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.

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.

Modelling the loss of genetic diversity in vole populations in a spatially and temporally varying environment

DEFF Research Database (Denmark)

Topping, Christopher John; Østergaard, Siri; Pertoldi, Cino

2003-01-01

conditions, but exclude factors such as animal behaviour, environmental structure, and breeding biology, all of which influence genetic diversity. Most populations are unique in some of these characteristics, and therefore may be unsuitable for the classical approach. Here, an alternative approach using...... to habitat availability and their influence on vole behaviour. Interaction between spatial and temporal dynamics altered the ratio of effective population size to census size. This indicates an altered reproductive potential, crucial in conservation biology applications. However, when the loss......Altering environmental conditions affects the genetic composition of populations via demographic and selective responses by creating of variety of population substructuring types. Classical genetic approaches can predict the genetic composition of populations under long-term or structurally stable...

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.

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

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.

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.

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.

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.

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

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...

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.

Shedding subspecies: The influence of genetics on reptile subspecies taxonomy.

Science.gov (United States)

Torstrom, Shannon M; Pangle, Kevin L; Swanson, Bradley J

2014-07-01

The subspecies concept influences multiple aspects of biology and management. The 'molecular revolution' altered traditional methods (morphological traits) of subspecies classification by applying genetic analyses resulting in alternative or contradictory classifications. We evaluated recent reptile literature for bias in the recommendations regarding subspecies status when genetic data were included. Reviewing characteristics of the study, genetic variables, genetic distance values and noting the species concepts, we found that subspecies were more likely elevated to species when using genetic analysis. However, there was no predictive relationship between variables used and taxonomic recommendation. There was a significant difference between the median genetic distance values when researchers elevated or collapsed a subspecies. Our review found nine different concepts of species used when recommending taxonomic change, and studies incorporating multiple species concepts were more likely to recommend a taxonomic change. Since using genetic techniques significantly alter reptile taxonomy there is a need to establish a standard method to determine the species-subspecies boundary in order to effectively use the subspecies classification for research and conservation purposes. Copyright © 2014 Elsevier Inc. All rights reserved.

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…

[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

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

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.

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.

The Effects of Predator Evolution and Genetic Variation on Predator-Prey Population-Level Dynamics.

Science.gov (United States)

Cortez, Michael H; Patel, Swati

2017-07-01

This paper explores how predator evolution and the magnitude of predator genetic variation alter the population-level dynamics of predator-prey systems. We do this by analyzing a general eco-evolutionary predator-prey model using four methods: Method 1 identifies how eco-evolutionary feedbacks alter system stability in the fast and slow evolution limits; Method 2 identifies how the amount of standing predator genetic variation alters system stability; Method 3 identifies how the phase lags in predator-prey cycles depend on the amount of genetic variation; and Method 4 determines conditions for different cycle shapes in the fast and slow evolution limits using geometric singular perturbation theory. With these four methods, we identify the conditions under which predator evolution alters system stability and shapes of predator-prey cycles, and how those effect depend on the amount of genetic variation in the predator population. We discuss the advantages and disadvantages of each method and the relations between the four methods. This work shows how the four methods can be used in tandem to make general predictions about eco-evolutionary dynamics and feedbacks.

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.

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.

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.

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.

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.

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

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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.

Genetic prediction of type 2 diabetes using deep neural network.

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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.

Multiple-Trait Genomic Selection Methods Increase Genetic Value Prediction Accuracy

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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

Genetic risk prediction and neurobiological understanding of alcoholism.

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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

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

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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

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

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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.

Logistics for Working Together to Facilitate Genomic/Quantitative Genetic Prediction

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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 ...

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

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

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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

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

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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.

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

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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

Do Staphylococcus epidermidis Genetic Clusters Predict Isolation Sources?

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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

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

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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...

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

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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

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

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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).

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

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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

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

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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

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

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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.

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

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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.

Genetic Testing for Respiratory Disease: Are We There Yet?

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Peter D Paré

2012-01-01

Full Text Available The human genome project promised a revolution in health care – the development of ‘personalized medicine’, where knowledge of an individual’s genetic code enables the prediction of risk for specific diseases and the potential to alter that risk based on preventive measures and lifestyle modification. The present brief review provides a report card on the progress toward that goal with respect to respiratory disease. Should generalized population screening for genetic risk factors for respiratory disease be instituted? Or not?

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

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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.

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

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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

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.

Epigenetic Alterations in Alzheimer's Disease

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Johannes eGräff

2015-12-01

Full Text Available Alzheimer’s disease (AD is the major cause of dementia in Western societies. It progresses asymptomatically during decades before being belatedly diagnosed when therapeutic strategies have become unviable. Although several genetic alterations have been associated with AD, the vast majority of AD cases do not show strong genetic underpinnings and are thus considered a consequence of non-genetic factors. Epigenetic mechanisms allow for the integration of long-lasting non-genetic inputs on specific genetic backgrounds, and recently, a growing number of epigenetic alterations in AD have been described. For instance, an accumulation of dysregulated epigenetic mechanisms in aging, the predominant risk factor of AD, might facilitate the onset of the disease. Likewise, mutations in several enzymes of the epigenetic machinery have been associated with neurodegenerative processes that are altered in AD such as impaired learning and memory formation. Genome-wide and locus-specific epigenetic alterations have also been reported, and several epigenetically dysregulated genes validated by independent groups. From these studies, a picture emerges of AD as being associated with DNA hypermethylation and histone deacetylation, suggesting a general repressed chromatin state and epigenetically reduced plasticity in AD. Here we review these recent findings and discuss several technical and methodological considerations that are imperative for their correct interpretation. We also pay particular focus on potential implementations and theoretical frameworks that we expect will help to better direct future studies aimed to unravel the epigenetic participation in AD.

Epigenetic Alterations in Alzheimer's Disease.

Science.gov (United States)

Sanchez-Mut, Jose V; Gräff, Johannes

2015-01-01

Alzheimer's disease (AD) is the major cause of dementia in Western societies. It progresses asymptomatically during decades before being belatedly diagnosed when therapeutic strategies have become unviable. Although several genetic alterations have been associated with AD, the vast majority of AD cases do not show strong genetic underpinnings and are thus considered a consequence of non-genetic factors. Epigenetic mechanisms allow for the integration of long-lasting non-genetic inputs on specific genetic backgrounds, and recently, a growing number of epigenetic alterations in AD have been described. For instance, an accumulation of dysregulated epigenetic mechanisms in aging, the predominant risk factor of AD, might facilitate the onset of the disease. Likewise, mutations in several enzymes of the epigenetic machinery have been associated with neurodegenerative processes that are altered in AD such as impaired learning and memory formation. Genome-wide and locus-specific epigenetic alterations have also been reported, and several epigenetically dysregulated genes validated by independent groups. From these studies, a picture emerges of AD as being associated with DNA hypermethylation and histone deacetylation, suggesting a general repressed chromatin state and epigenetically reduced plasticity in AD. Here we review these recent findings and discuss several technical and methodological considerations that are imperative for their correct interpretation. We also pay particular focus on potential implementations and theoretical frameworks that we expect will help to better direct future studies aimed to unravel the epigenetic participation in AD.

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...

Genetic diversity and connectivity within Mytilus spp. in the subarctic and Arctic

DEFF Research Database (Denmark)

Mathiesen, Sofie Smedegaard; Thyrring, Jakob; Hansen, Jakob Hemmer

2017-01-01

Climate changes in the Arctic are predicted to alter distributions of marine species. However, such changes are difficult to quantify because information on present species distribution and the genetic variation within species is lacking or poorly examined. Blue mussels, Mytilus spp., are ecosystem...... engineers in the coastal zone globally. To improve knowledge of distribution and genetic structure of the Mytilus edulis complex in the Arctic, we analyzed 81 SNPs in 534 Mytilus spp. individuals sampled at 13 sites to provide baseline data for distribution and genetic variation of Mytilus mussels...

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.

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

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

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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.

Predictive value of testing for multiple genetic variants in multifactorial diseases: implications for the discourse on ethical, legal and social issues

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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.

[Epigenetic alterations in acute lymphoblastic leukemia].

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Navarrete-Meneses, María Del Pilar; Pérez-Vera, Patricia

Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. It is well-known that genetic alterations constitute the basis for the etiology of ALL. However, genetic abnormalities are not enough for the complete development of the disease, and additional alterations such as epigenetic modifications are required. Such alterations, like DNA methylation, histone modifications, and noncoding RNA regulation have been identified in ALL. DNA hypermethylation in promoter regions is one of the most frequent epigenetic modifications observed in ALL. This modification frequently leads to gene silencing in tumor suppressor genes, and in consequence, contributes to leukemogenesis. Alterations in histone remodeling proteins have also been detected in ALL, such as the overexpression of histone deacetylases enzymes, and alteration of acetyltransferases and methyltransferases. ALL also shows alteration in the expression of miRNAs, and in consequence, the modification in the expression of their target genes. All of these epigenetic modifications are key events in the malignant transformation since they lead to the deregulation of oncogenes as BLK, WNT5B and WISP1, and tumor suppressors such as FHIT, CDKN2A, CDKN2B, and TP53, which alter fundamental cellular processes and potentially lead to the development of ALL. Both genetic and epigenetic alterations contribute to the development and evolution of ALL. Copyright © 2017 Hospital Infantil de México Federico Gómez. Publicado por Masson Doyma México S.A. All rights reserved.

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

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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

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

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.

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.

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

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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.

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.

Epigenetic Alterations in Alzheimer’s Disease

Science.gov (United States)

Sanchez-Mut, Jose V.; Gräff, Johannes

2015-01-01

Alzheimer’s disease (AD) is the major cause of dementia in Western societies. It progresses asymptomatically during decades before being belatedly diagnosed when therapeutic strategies have become unviable. Although several genetic alterations have been associated with AD, the vast majority of AD cases do not show strong genetic underpinnings and are thus considered a consequence of non-genetic factors. Epigenetic mechanisms allow for the integration of long-lasting non-genetic inputs on specific genetic backgrounds, and recently, a growing number of epigenetic alterations in AD have been described. For instance, an accumulation of dysregulated epigenetic mechanisms in aging, the predominant risk factor of AD, might facilitate the onset of the disease. Likewise, mutations in several enzymes of the epigenetic machinery have been associated with neurodegenerative processes that are altered in AD such as impaired learning and memory formation. Genome-wide and locus-specific epigenetic alterations have also been reported, and several epigenetically dysregulated genes validated by independent groups. From these studies, a picture emerges of AD as being associated with DNA hypermethylation and histone deacetylation, suggesting a general repressed chromatin state and epigenetically reduced plasticity in AD. Here we review these recent findings and discuss several technical and methodological considerations that are imperative for their correct interpretation. We also pay particular focus on potential implementations and theoretical frameworks that we expect will help to better direct future studies aimed to unravel the epigenetic participation in AD. PMID:26734709

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.

Short communication: Alteration of priors for random effects in Gaussian linear mixed model

DEFF Research Database (Denmark)

Vandenplas, Jérémie; Christensen, Ole Fredslund; Gengler, Nicholas

2014-01-01

such alterations. Therefore, the aim of this study was to propose a method to alter both the mean and (co)variance of the prior multivariate normal distributions of random effects of linear mixed models while using currently available software packages. The proposed method was tested on simulated examples with 3......, multiple-trait predictions of lactation yields, and Bayesian approaches integrating external information into genetic evaluations) need to alter both the mean and (co)variance of the prior distributions and, to our knowledge, most software packages available in the animal breeding community do not permit...... different software packages available in animal breeding. The examples showed the possibility of the proposed method to alter both the mean and (co)variance of the prior distributions with currently available software packages through the use of an extended data file and a user-supplied (co)variance matrix....

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.

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

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.

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

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

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

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.

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.

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.

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.

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.

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.

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.

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.

Shape: automatic conformation prediction of carbohydrates using a genetic algorithm

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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.

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.

Predicting life-history adaptations to pollutants

Energy Technology Data Exchange (ETDEWEB)

Maltby, L. [Univ. of Sheffield (United Kingdom). Dept. of Animal and Plant Sciences

1995-12-31

Animals may adapt to pollutant stress so that individuals from polluted environments are less susceptible than those from unpolluted environments. In addition to such direct adaptations, animals may respond to pollutant stress by life-history modifications; so-called indirect adaptations. This paper will demonstrate how, by combining life-history theory and toxicological data, it is possible to predict stress-induced alterations in reproductive output and offspring size. Pollutant-induced alterations in age-specific survival in favor of adults and reductions in juvenile growth, conditions are predicted to select for reduced investment in reproduction and the allocation of this investment into fewer, larger offspring. Field observations on the freshwater crustaceans, Asellus aquaticus and Gammarus pulex, support these predictions. Females from metal-polluted sites had lower investment in reproduction and produced larger offspring than females of the same species from unpolluted sites. Moreover, interpopulation differences in reproductive biology persisted in laboratory cultures indicating that they had a genetic basis and were therefore due to adaptation rather than acclimation. The general applicability of this approach will be considered.

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.

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.

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.

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

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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

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

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.

Genetic variation in adaptability and pleiotropy in budding yeast.

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Jerison, Elizabeth R; Kryazhimskiy, Sergey; Mitchell, James Kameron; Bloom, Joshua S; Kruglyak, Leonid; Desai, Michael M

2017-08-17

Evolution can favor organisms that are more adaptable, provided that genetic variation in adaptability exists. Here, we quantify this variation among 230 offspring of a cross between diverged yeast strains. We measure the adaptability of each offspring genotype, defined as its average rate of adaptation in a specific environmental condition, and analyze the heritability, predictability, and genetic basis of this trait. We find that initial genotype strongly affects adaptability and can alter the genetic basis of future evolution. Initial genotype also affects the pleiotropic consequences of adaptation for fitness in a different environment. This genetic variation in adaptability and pleiotropy is largely determined by initial fitness, according to a rule of declining adaptability with increasing initial fitness, but several individual QTLs also have a significant idiosyncratic role. Our results demonstrate that both adaptability and pleiotropy are complex traits, with extensive heritable differences arising from naturally occurring variation.

[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.

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.

Genetic Testing in Psychiatry: A Review of Attitudes and Beliefs

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Lawrence, Ryan E; Appelbaum, Paul S.

2012-01-01

The advent of genetic testing for psychiatric conditions raises difficult questions about when and how the tests should be used. Development of policies regarding these issues may be informed in a variety of ways by the views of key stakeholders: patients, family members, healthcare professionals, and the general public. Here we review empirical studies of attitudes towards genetic testing among these groups. Patients and family members show strong interest in diagnostic and predictive genetic testing, and to a considerable extent psychiatrists share their enthusiasm. Prenatal test utilization seems likely to depend both on parental views on abortion and the seriousness of the disorder. Parents show a surprising degree of interest in predictive testing of children, even when there are no preventive interventions available. Many persons report themselves ready to alter their lifestyles and plans for marriage and family in response to test results. Respondents also fear negative consequences, from discrimination to being unable to cope with knowledge of their “genetic fate.” Empirical studies of beliefs about genetic testing suggest tests are likely to be embraced widely, but the studies have methodologic limitations, reducing the certainty of their conclusions, and indicating a need for further research with more representative samples. PMID:22168293

Novel genetic variants in miR-191 gene and familial ovarian cancer

International Nuclear Information System (INIS)

Shen, Jie; DiCioccio, Richard; Odunsi, Kunle; Lele, Shashikant B; Zhao, Hua

2010-01-01

Half of the familial aggregation of ovarian cancer can't be explained by any known risk genes, suggesting the existence of other genetic risk factors. Some of these unknown factors may not be traditional protein encoding genes. MicroRNA (miRNA) plays a critical role in tumorigenesis, but it is still unknown if variants in miRNA genes lead to predisposition to cancer. Considering the fact that miRNA regulates a number of tumor suppressor genes (TSGs) and oncogenes, genetic variations in miRNA genes could affect the levels of expression of TSGs or oncogenes and, thereby, cancer risk. To test this hypothesis in familial ovarian cancer, we screened for genetic variants in thirty selected miRNA genes, which are predicted to regulate key ovarian cancer genes and are reported to be misexpressed in ovarian tumor tissues, in eighty-three patients with familial ovarian cancer. All of the patients are non-carriers of any known BRCA1/2 or mismatch repair (MMR) gene mutations. Seven novel genetic variants were observed in four primary or precursor miRNA genes. Among them, three rare variants were found in the precursor or primary precursor of the miR-191 gene. In functional assays, the one variant located in the precursor of miR-191 resulted in conformational changes in the predicted secondary structures, and consequently altered the expression of mature miR-191. In further analysis, we found that this particular variant exists in five family members who had ovarian cancer. Our findings suggest that there are novel genetic variants in miRNA genes, and those certain genetic variants in miRNA genes can affect the expression of mature miRNAs and, consequently, might alter the regulation of TSGs or oncogenes. Additionally, the variant might be potentially associated with the development of familial ovarian cancer

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.

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.

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

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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.

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

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/

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

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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.

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

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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

Epilepsy in patients with GRIN2A alterations

DEFF Research Database (Denmark)

von Stülpnagel, Celina; Ensslen, M; Møller, R S

2017-01-01

indicate that children with epilepsy due to pathogenic GRIN2A mutations present with different clinical phenotypes and a spectrum of seizure types in the context of a pharmacoresistant epilepsy providing information for clinicians treating children with this form of genetically determined epileptic......OBJECTIVE: To delineate the genetic, neurodevelopmental and epileptic spectrum associated with GRIN2A alterations with emphasis on epilepsy treatment. METHODS: Retrospective study of 19 patients (7 females; age: 1-38 years; mean 10.1 years) with epilepsy and GRIN2A alteration. Genetic variants were...... classified according to the guidelines and recommendations of the American College of Medical Genetics (ACMG). Clinical findings including epilepsy classification, treatment, EEG findings, early childhood development and neurodevelopmental outcome were collected with an electronic questionnaire. RESULTS: 7...

Genetic Differences in the Immediate Transcriptome Response to Stress Predict Risk-Related Brain Function and Psychiatric Disorders

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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

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

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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.…

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.

Present, past and future of the European rock fern Asplenium fontanum: combining distribution modelling and population genetics to study the effect of climate change on geographic range and genetic diversity.

Science.gov (United States)

Bystriakova, Nadia; Ansell, Stephen W; Russell, Stephen J; Grundmann, Michael; Vogel, Johannes C; Schneider, Harald

2014-02-01

Climate change is expected to alter the geographic range of many plant species dramatically. Predicting this response will be critical to managing the conservation of plant resources and the effects of invasive species. The aim of this study was to predict the response of temperate homosporous ferns to climate change. Genetic diversity and changes in distribution range were inferred for the diploid rock fern Asplenium fontanum along a South-North transect, extending from its putative last glacial maximum (LGM) refugia in southern France towards southern Germany and eastern-central France. This study reconciles observations from distribution models and phylogeographic analyses derived from plastid and nuclear diversity. Genetic diversity distribution and niche modelling propose that genetic diversity accumulates in the LGM climate refugium in southern France with the formation of a diversity gradient reflecting a slow, post-LGM range expansion towards the current distribution range. Evidence supports the fern's preference for outcrossing, contradicting the expectation that homosporous ferns would populate new sites by single-spore colonization. Prediction of climate and distribution range change suggests that a dramatic loss of range and genetic diversity in this fern is possible. The observed migration is best described by the phalanx expansion model. The results suggest that homosporous ferns reproducing preferentially by outcrossing accumulate genetic diversity primarily in LGM climate refugia and may be threatened if these areas disappear due to global climate change.

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.

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

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.

Genetic and Clinical Characteristics of Phyllodes Tumors of the Breast

Directory of Open Access Journals (Sweden)

Ji-Yeon Kim

2018-02-01

Full Text Available PURPOSE: Phyllodes tumors (PTs of the breast are rare, accounting for less than 1% of all breast tumors. Among PTs, malignant PTs (MPTs have malignant characteristics and distant metastases occur in about 20% to 30% of MPTs. However, there is no effective treatment for MPTs with distant metastasis, resulting in an abject prognosis. We performed targeted deep sequencing on PTs to identify the associations between genetic alterations and clinical prognosis. METHODS: We performed targeted deep sequencing to evaluate the genetic characteristics of PTs and analyzed the relationships between clinical and genetic characteristics. RESULTS: A total of 17 PTs were collected between 2001 and 2012. Histologic review was performed by pathologists. The samples included three benign PTs, one borderline PT, and 13 MPTs. The most frequently detected genetic alteration occurred in the TERT promoter region (70.6%, followed by MED12 (64.7%. EGFR amplification and TP53 alteration were detected in four MPTs without genetic alterations in MED12 and TERT promoter regions. Genetic alterations of RARA and ZNF703 were repeatedly found in PTs with local recurrence, and genetic alterations of SETD2, BRCA2, and TSC1 were detected in PTs with distant metastasis. Especially, MPT harboring PTEN and RB1 copy number deletion showed rapid disease progression. CONCLUSIONS: In this study, we provide genetic characterization and potential therapeutic target for this rare, potentially lethal disease. Further large-scale comprehensive genetic study and functional validation are warranted.

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.

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.

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.

Melanoma genetics

DEFF Research Database (Denmark)

Read, Jazlyn; Wadt, Karin A W; Hayward, Nicholas K

2015-01-01

Approximately 10% of melanoma cases report a relative affected with melanoma, and a positive family history is associated with an increased risk of developing melanoma. Although the majority of genetic alterations associated with melanoma development are somatic, the underlying presence of herita......Approximately 10% of melanoma cases report a relative affected with melanoma, and a positive family history is associated with an increased risk of developing melanoma. Although the majority of genetic alterations associated with melanoma development are somatic, the underlying presence...... in a combined total of approximately 50% of familial melanoma cases, the underlying genetic basis is unexplained for the remainder of high-density melanoma families. Aside from the possibility of extremely rare mutations in a few additional high penetrance genes yet to be discovered, this suggests a likely...... polygenic component to susceptibility, and a unique level of personal melanoma risk influenced by multiple low-risk alleles and genetic modifiers. In addition to conferring a risk of cutaneous melanoma, some 'melanoma' predisposition genes have been linked to other cancers, with cancer clustering observed...

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.

Predicting effects of noncoding variants with deep learning-based sequence model.

Science.gov (United States)

Zhou, Jian; Troyanskaya, Olga G

2015-10-01

Identifying functional effects of noncoding variants is a major challenge in human genetics. To predict the noncoding-variant effects de novo from sequence, we developed a deep learning-based algorithmic framework, DeepSEA (http://deepsea.princeton.edu/), that directly learns a regulatory sequence code from large-scale chromatin-profiling data, enabling prediction of chromatin effects of sequence alterations with single-nucleotide sensitivity. We further used this capability to improve prioritization of functional variants including expression quantitative trait loci (eQTLs) and disease-associated variants.

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.

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

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.

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

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.

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).

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.

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.

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.

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.

Aqueous alteration of Japanese simulated waste glass P0798: Effects of alteration-phase formation on alteration rate and cesium retention

International Nuclear Information System (INIS)

Inagaki, Y.; Shinkai, A.; Idemistu, K.; Arima, T.; Yoshikawa, H.; Yui, M.

2006-01-01

Aqueous alteration tests were performed with a Japanese simulated waste glass P0798 in alkaline solutions as a function of pH or species/concentration of alkaline metals in the solution in order to evaluate the alteration conditions determining whether smectite (2:1 clay mineral) or analcime (zeolite) forms as the major alteration-phase. XRD analysis of the alteration-phases showed that smectite forms at any pH between 9.5 and 12, and analcime forms at pH above 11, though the formation also depends on species and concentrations of alkaline metals in the solution. These results cannot agree with the thermodynamically predicted phase stability, e.g., smectite is more stable than the thermodynamic prediction shows. On the basis of the results of alteration conditions, the alteration tests were performed under smectite forming conditions, where only smectite forms or no crystalline phases form, in order to evaluate the alteration rate and the mechanism of cesium release/retention. The results showed that the glass alteration proceeds slowly in proportion to square root of time under smectite forming conditions, which indicates that the alteration rate can be controlled by a diffusion process. It was suggested that the alteration rate under smectite forming conditions is independent of the pH, alkaline metal species/concentration in the solution and whether smectite actually forms or not. The results also indicated that most of cesium dissolved from the glass can be retained in the alteration-phases by reversible sorption onto smectite or irreversible incorporation into analcime, pollucite or solid solutions of them

Relations of mitochondrial genetic variants to measures of vascular function.

Science.gov (United States)

Fetterman, Jessica L; Liu, Chunyu; Mitchell, Gary F; Vasan, Ramachandran S; Benjamin, Emelia J; Vita, Joseph A; Hamburg, Naomi M; Levy, Daniel

2018-05-01

Mitochondrial genetic variation with resultant alterations in oxidative phosphorylation may influence vascular function and contribute to cardiovascular disease susceptibility. We assessed relations of peptide-encoding variants in the mitochondrial genome with measures of vascular function in Framingham Heart Study participants. Of 258 variants assessed, 40 were predicted to have functional consequences by bioinformatics programs. A maternal pattern of heritability was estimated to contribute to the variability of aortic stiffness. A putative association with a microvascular function measure was identified that requires replication. The methods we have developed can be applied to assess the relations of mitochondrial genetic variation to other phenotypes. Copyright © 2017 Elsevier B.V. and Mitochondria Research Society. All rights reserved.

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.

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.

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.

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.

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.

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.

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

Radiation protection philosophy alters

International Nuclear Information System (INIS)

Firmin, G.

1977-01-01

Two significant events that have taken place this year in the field of radiation protection are reported. New SI units have been proposed (and effectively adopted), and the ICRP has revised its recommendations. Changes of emphasis in the latest recommendations (ICRP Publication 26) imply an altered radiation protection philosophy, in particular the relation of dose limits to estimates of average risk, an altered view of the critical organ approach and a new attitude to genetic dose to the population. (author)

Analysis of conditional genetic effects and variance components in developmental genetics.

Science.gov (United States)

Zhu, J

1995-12-01

A genetic model with additive-dominance effects and genotype x environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t-1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects.

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.

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

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)

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.

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

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.

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.

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.

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.

Comparison of whole-genome prediction models for traits with contrasting genetic architecture in a diversity panel of maize inbred lines

Directory of Open Access Journals (Sweden)

Riedelsheimer Christian

2012-09-01

Full Text Available Abstract Background There is increasing empirical evidence that whole-genome prediction (WGP is a powerful tool for predicting line and hybrid performance in maize. However, there is a lack of knowledge about the sensitivity of WGP models towards the genetic architecture of the trait. Whereas previous studies exclusively focused on highly polygenic traits, important agronomic traits such as disease resistances, nutrifunctional or climate adaptational traits have a genetic architecture which is either much less complex or unknown. For such cases, information about model robustness and guidelines for model selection are lacking. Here, we compared five WGP models with different assumptions about the distribution of the underlying genetic effects. As contrasting model traits, we chose three highly polygenic agronomic traits and three metabolites each with a major QTL explaining 22 to 30% of the genetic variance in a panel of 289 diverse maize inbred lines genotyped with 56,110 SNPs. Results We found the five WGP models to be remarkable robust towards trait architecture with the largest differences in prediction accuracies ranging between 0.05 and 0.14 for the same trait, most likely as the result of the high level of linkage disequilibrium prevailing in elite maize germplasm. Whereas RR-BLUP performed best for the agronomic traits, it was inferior to LASSO or elastic net for the three metabolites. We found the approach of genome partitioning of genetic variance, first applied in human genetics, as useful in guiding the breeder which model to choose, if prior knowledge of the trait architecture is lacking. Conclusions Our results suggest that in diverse germplasm of elite maize inbred lines with a high level of LD, WGP models differ only slightly in their accuracies, irrespective of the number and effects of QTL found in previous linkage or association mapping studies. However, small gains in prediction accuracies can be achieved if the WGP model is

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.

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...

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

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

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.

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

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.

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.

The psychological complexity of predictive testing for late onset neurogenetic diseases and hereditary cancers: implications for multidisciplinary counselling and for genetic education.

Science.gov (United States)

Evers-Kiebooms, G; Welkenhuysen, M; Claes, E; Decruyenaere, M; Denayer, L

2000-09-01

Increasing knowledge about the human genome has resulted in the availability of a steadily increasing number of predictive DNA-tests for two major categories of diseases: neurogenetic diseases and hereditary cancers. The psychological complexity of predictive testing for these late onset diseases requires careful consideration. It is the main aim of the present paper to describe this psychological complexity, which necessitates an adequate and systematic multidisciplinary approach, including psychological counselling, as well as ongoing education of professionals and of the general public. Predictive testing for neurogenetic diseases--in an adequate counselling context--so far elicits optimism regarding the short- and mid-term impact of the predictive test result. The psychosocial impact has been most widely studied for Huntington's disease. Longitudinal studies are of the utmost importance in evaluating the long-term impact of predictive testing for neurogenetic diseases on the tested person and his/her family. Given the more recent experience with predictive DNA-testing for hereditary cancers, fewer published scientific data are available. Longitudinal research on the mid- and long-term psychological impact of the predictive test result is essential. Decision making regarding health surveillance or preventive surgery after being detected as a carrier of one of the relevant mutations should receive special attention. Tailoring the professional approach--inside and outside genetic centres--to the families' needs is a continuous challenge. Even if a continuous effort is made, several important questions remain unanswered, last but not least the question regarding the best strategy to guarantee that the availability of predictive genetic testing results in a reduction of suffering caused by genetic disease and in an improvement of the quality of life of families confronted with genetic disease.

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

Genetically Predicted Body Mass Index and Breast Cancer Risk: Mendelian Randomization Analyses of Data from 145,000 Women of European Descent.

Directory of Open Access Journals (Sweden)

Yan Guo

2016-08-01

Full Text Available 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 environmental factors.We applied Mendelian randomization to evaluate the association between BMI and risk of breast cancer occurrence using data from two large breast cancer consortia. We created a weighted BMI genetic score comprising 84 BMI-associated genetic variants to predicted BMI. We evaluated genetically predicted BMI in association with breast cancer risk using individual-level data from the Breast Cancer Association Consortium (BCAC (cases  =  46,325, controls  =  42,482. We further evaluated the association between genetically predicted BMI and breast cancer risk using summary statistics from 16,003 cases and 41,335 controls from the Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE Project. Because most studies measured BMI after cancer diagnosis, we could not conduct a parallel analysis to adequately evaluate the association of measured BMI with breast cancer risk prospectively.In the BCAC data, genetically predicted BMI was found to be inversely associated with breast cancer risk (odds ratio [OR]  =  0.65 per 5 kg/m2 increase, 95% confidence interval [CI]: 0.56-0.75, p = 3.32 × 10-10. The associations were similar for both premenopausal (OR   =   0.44, 95% CI:0.31-0.62, p  =  9.91 × 10-8 and postmenopausal breast cancer (OR  =  0.57, 95% CI: 0.46-0.71, p  =  1.88 × 10-8. This association was replicated in the data from the DRIVE consortium (OR  =  0.72, 95% CI: 0.60-0.84, p   =   1.64 × 10-7. Single marker analyses identified 17 of the 84 BMI-associated single nucleotide polymorphisms (SNPs in association with breast cancer risk at p < 0.05; for 16 of them, the

Genetic Alterations in Intervertebral Disc Disease

Directory of Open Access Journals (Sweden)

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

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

Neural networks for predicting breeding values and genetic gains

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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.

What Are the Predictors of Altered Central Pain Modulation in Chronic Musculoskeletal Pain Populations? A Systematic Review.

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Clark, Jacqui; Nijs, Jo; Yeowell, Gillian; Goodwin, Peter Charles

2017-09-01

Altered central pain modulation is the predominant pain mechanism in a proportion of chronic musculoskeletal pain disorders and is associated with poor outcomes. Although existing studies predict poor outcomes such as persistent pain and disability, to date there is little consensus on what factors specifically predict altered central pain modulation. To review the existing literature on the predictive factors specifically for altered central pain modulation in musculoskeletal pain populations. This is a systematic review in accordance with supplemented PRISMA guidelines. A systematic search was performed by 2 mutually blinded reviewers. Relevant articles were screened by title and abstract from Medline, Embase, PubMed, CINAHL, and Web of Science electronic databases. Alternative sources were also sought to locate missed potential articles. Eligibility included studies published in English, adults aged 18 to 65, musculoskeletal pain, baseline measurements taken at the pre-morbid or acute stage, > 3-month follow-up time after pain onset, and primary outcome measures specific to altered central pain modulation. Studies were excluded where there were concurrent diseases or they were non-predictive studies. Risk of bias was assessed using the quality in prognostic studies (QUIPS) tool. Study design, demographics, musculoskeletal region, inclusion/exclusion criteria, measurement timelines, predictor and primary outcome measures, and results were extracted. Data were synthesized qualitatively and strength of evidence was scored using the grading of recommendations, assessment, development, and evaluations (GRADE) scoring system. Nine eligible articles were located, in various musculoskeletal populations (whiplash, n = 2; widespread pain, n = 5; temporomandibular disorder, n = 2). Moderate evidence was found for 2 predictive factors of altered central pain modulation: 1) high sensory sensitivity (using genetic testing or quantitative sensory tests), and 2) psychological

Narcissism predicts impulsive buying: phenotypic and genetic evidence

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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

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.

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.

Current and historical drivers of landscape genetic structure differ in core and peripheral salamander populations.

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Rachael Y Dudaniec

Full Text Available With predicted decreases in genetic diversity and greater genetic differentiation at range peripheries relative to their cores, it can be difficult to distinguish between the roles of current disturbance versus historic processes in shaping contemporary genetic patterns. To address this problem, we test for differences in historic demography and landscape genetic structure of coastal giant salamanders (Dicamptodon tenebrosus in two core regions (Washington State, United States versus the species' northern peripheral region (British Columbia, Canada where the species is listed as threatened. Coalescent-based demographic simulations were consistent with a pattern of post-glacial range expansion, with both ancestral and current estimates of effective population size being much larger within the core region relative to the periphery. However, contrary to predictions of recent human-induced population decline in the less genetically diverse peripheral region, there was no genetic signature of population size change. Effects of current demographic processes on genetic structure were evident using a resistance-based landscape genetics approach. Among core populations, genetic structure was best explained by length of the growing season and isolation by resistance (i.e. a 'flat' landscape, but at the periphery, topography (slope and elevation had the greatest influence on genetic structure. Although reduced genetic variation at the range periphery of D. tenebrosus appears to be largely the result of biogeographical history rather than recent impacts, our analyses suggest that inherent landscape features act to alter dispersal pathways uniquely in different parts of the species' geographic range, with implications for habitat management.

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

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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.

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.

Genetics of Common Endocrine Disease: The Present and the Future.

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Goodarzi, Mark O

2016-03-01

In honor of the 75th issue of the Journal of Clinical Endocrinology and Metabolism, the author was invited to present his perspectives on genetics in human endocrinology. This paper reviews what the field has achieved in the genetics of common endocrine disease, and offers predictions on where the field will move in the future and its impact on endocrine clinical practice. The October 2015 data release of the National Human Genome Research Institute-European Bioinformatics Institute (NHGRI-EBI) Catalog of Published Genome-wide Association Studies was queried regarding endocrinologic diseases and traits. PubMed searches were focused on genetic prediction of disease, genetic findings and drug targets, functional interrogation of genetic loci, use of genetics to subtype disease, missing heritability, systems genomics, and higher order chromatin structures as regulators of gene function. Nearly a quarter of genome wide association study findings concern endocrinologic diseases and traits. While these findings have not yet dramatically altered clinical care, genetics will have a major impact by providing the drug targets of tomorrow, facilitated by experimental and bioinformatic advances that will shorten the time from gene discovery to drug development. Use of genetic findings to subtype common endocrine disease will allow more precise prevention and treatment efforts. Future advances will allow us to move away from the common view of DNA as a string of letters, allowing exploration of higher order structure that likely explains much "missing heritability." The future will see a greater role of genetics at the bedside, with genetic epidemiologic discoveries leading not only to new treatments of endocrine disease, but also helping us prescribe the right drug to the right patients by allowing subclassification of common heterogeneous endocrine conditions. Future technological breakthroughs will reveal the heritable mysteries hidden in chromatin structure, leading to a

Genetic and epigenetic markers in colorectal cancer screening: recent advances.

Science.gov (United States)

Singh, Manish Pratap; Rai, Sandhya; Suyal, Shradha; Singh, Sunil Kumar; Singh, Nand Kumar; Agarwal, Akash; Srivastava, Sameer

2017-07-01

Colorectal cancer (CRC) is a heterogenous disease which develops from benign intraepithelial lesions known as adenomas to malignant carcinomas. Acquired alterations in Wnt signaling, TGFβ, MAPK pathway genes and clonal propagation of altered cells are responsible for this transformation. Detection of adenomas or early stage cancer in asymptomatic patients and better prognostic and predictive markers is important for improving the clinical management of CRC. Area covered: In this review, the authors have evaluated the potential of genetic and epigenetic alterations as markers for early detection, prognosis and therapeutic predictive potential in the context of CRC. We have discussed molecular heterogeneity present in CRC and its correlation to prognosis and response to therapy. Expert commentary: Molecular marker based CRC screening methods still fail to gain trust of clinicians. Invasive screening methods, molecular heterogeneity, chemoresistance and low quality test samples are some key challenges which need to be addressed in the present context. New sequencing technologies and integrated omics data analysis of individual or population cohort results in GWAS. MPE studies following a GWAS could be future line of research to establish accurate correlations between CRC and its risk factors. This strategy would identify most reliable biomarkers for CRC screening and management.

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.

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.

A semi-supervised learning approach to predict synthetic genetic interactions by combining functional and topological properties of functional gene network

Directory of Open Access Journals (Sweden)

Han Kyungsook

2010-06-01

Full Text Available Abstract Background Genetic interaction profiles are highly informative and helpful for understanding the functional linkages between genes, and therefore have been extensively exploited for annotating gene functions and dissecting specific pathway structures. However, our understanding is rather limited to the relationship between double concurrent perturbation and various higher level phenotypic changes, e.g. those in cells, tissues or organs. Modifier screens, such as synthetic genetic arrays (SGA can help us to understand the phenotype caused by combined gene mutations. Unfortunately, exhaustive tests on all possible combined mutations in any genome are vulnerable to combinatorial explosion and are infeasible either technically or financially. Therefore, an accurate computational approach to predict genetic interaction is highly desirable, and such methods have the potential of alleviating the bottleneck on experiment design. Results In this work, we introduce a computational systems biology approach for the accurate prediction of pairwise synthetic genetic interactions (SGI. First, a high-coverage and high-precision functional gene network (FGN is constructed by integrating protein-protein interaction (PPI, protein complex and gene expression data; then, a graph-based semi-supervised learning (SSL classifier is utilized to identify SGI, where the topological properties of protein pairs in weighted FGN is used as input features of the classifier. We compare the proposed SSL method with the state-of-the-art supervised classifier, the support vector machines (SVM, on a benchmark dataset in S. cerevisiae to validate our method's ability to distinguish synthetic genetic interactions from non-interaction gene pairs. Experimental results show that the proposed method can accurately predict genetic interactions in S. cerevisiae (with a sensitivity of 92% and specificity of 91%. Noticeably, the SSL method is more efficient than SVM, especially for

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.

Genetic influences on functional connectivity associated with feedback processing and prediction error: Phase coupling of theta-band oscillations in twins.

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Demiral, Şükrü Barış; Golosheykin, Simon; Anokhin, Andrey P

2017-05-01

Detection and evaluation of the mismatch between the intended and actually obtained result of an action (reward prediction error) is an integral component of adaptive self-regulation of behavior. Extensive human and animal research has shown that evaluation of action outcome is supported by a distributed network of brain regions in which the anterior cingulate cortex (ACC) plays a central role, and the integration of distant brain regions into a unified feedback-processing network is enabled by long-range phase synchronization of cortical oscillations in the theta band. Neural correlates of feedback processing are associated with individual differences in normal and abnormal behavior, however, little is known about the role of genetic factors in the cerebral mechanisms of feedback processing. Here we examined genetic influences on functional cortical connectivity related to prediction error in young adult twins (age 18, n=399) using event-related EEG phase coherence analysis in a monetary gambling task. To identify prediction error-specific connectivity pattern, we compared responses to loss and gain feedback. Monetary loss produced a significant increase of theta-band synchronization between the frontal midline region and widespread areas of the scalp, particularly parietal areas, whereas gain resulted in increased synchrony primarily within the posterior regions. Genetic analyses showed significant heritability of frontoparietal theta phase synchronization (24 to 46%), suggesting that individual differences in large-scale network dynamics are under substantial genetic control. We conclude that theta-band synchronization of brain oscillations related to negative feedback reflects genetically transmitted differences in the neural mechanisms of feedback processing. To our knowledge, this is the first evidence for genetic influences on task-related functional brain connectivity assessed using direct real-time measures of neuronal synchronization. Copyright © 2016

A genome-wide screen for genetic variants that modify the recruitment of REST to its target genes.

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Rory Johnson

Full Text Available Increasing numbers of human diseases are being linked to genetic variants, but our understanding of the mechanistic links leading from DNA sequence to disease phenotype is limited. The majority of disease-causing nucleotide variants fall within the non-protein-coding portion of the genome, making it likely that they act by altering gene regulatory sequences. We hypothesised that SNPs within the binding sites of the transcriptional repressor REST alter the degree of repression of target genes. Given that changes in the effective concentration of REST contribute to several pathologies-various cancers, Huntington's disease, cardiac hypertrophy, vascular smooth muscle proliferation-these SNPs should alter disease-susceptibility in carriers. We devised a strategy to identify SNPs that affect the recruitment of REST to target genes through the alteration of its DNA recognition element, the RE1. A multi-step screen combining genetic, genomic, and experimental filters yielded 56 polymorphic RE1 sequences with robust and statistically significant differences of affinity between alleles. These SNPs have a considerable effect on the the functional recruitment of REST to DNA in a range of in vitro, reporter gene, and in vivo analyses. Furthermore, we observe allele-specific biases in deeply sequenced chromatin immunoprecipitation data, consistent with predicted differenes in RE1 affinity. Amongst the targets of polymorphic RE1 elements are important disease genes including NPPA, PTPRT, and CDH4. Thus, considerable genetic variation exists in the DNA motifs that connect gene regulatory networks. Recently available ChIP-seq data allow the annotation of human genetic polymorphisms with regulatory information to generate prior hypotheses about their disease-causing mechanism.

A Genome-Wide Screen for Genetic Variants That Modify the Recruitment of REST to Its Target Genes

Science.gov (United States)

Johnson, Rory; Richter, Nadine; Bogu, Gireesh K.; Bhinge, Akshay; Teng, Siaw Wei; Choo, Siew Hua; Andrieux, Lise O.; de Benedictis, Cinzia; Jauch, Ralf; Stanton, Lawrence W.

2012-01-01

Increasing numbers of human diseases are being linked to genetic variants, but our understanding of the mechanistic links leading from DNA sequence to disease phenotype is limited. The majority of disease-causing nucleotide variants fall within the non-protein-coding portion of the genome, making it likely that they act by altering gene regulatory sequences. We hypothesised that SNPs within the binding sites of the transcriptional repressor REST alter the degree of repression of target genes. Given that changes in the effective concentration of REST contribute to several pathologies—various cancers, Huntington's disease, cardiac hypertrophy, vascular smooth muscle proliferation—these SNPs should alter disease-susceptibility in carriers. We devised a strategy to identify SNPs that affect the recruitment of REST to target genes through the alteration of its DNA recognition element, the RE1. A multi-step screen combining genetic, genomic, and experimental filters yielded 56 polymorphic RE1 sequences with robust and statistically significant differences of affinity between alleles. These SNPs have a considerable effect on the the functional recruitment of REST to DNA in a range of in vitro, reporter gene, and in vivo analyses. Furthermore, we observe allele-specific biases in deeply sequenced chromatin immunoprecipitation data, consistent with predicted differenes in RE1 affinity. Amongst the targets of polymorphic RE1 elements are important disease genes including NPPA, PTPRT, and CDH4. Thus, considerable genetic variation exists in the DNA motifs that connect gene regulatory networks. Recently available ChIP–seq data allow the annotation of human genetic polymorphisms with regulatory information to generate prior hypotheses about their disease-causing mechanism. PMID:22496669

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....

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

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

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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.

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

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

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

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

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.

Commercialization of genetic testing services: the FDA, market forces, and biological tarot cards.

Science.gov (United States)

Malinowski, M J; Blatt, R J R

1997-03-01

Many women fear being diagnosed with breast cancer, and rightfully so. Despite the capabilities of modern medicine, the cumulative lifetime risk of getting the disease has risen to one in eight and, despite decades of research, no cures exist. In this Article, the authors explore the commercialization of so-called breast cancer gene tests, based upon genetic alterations linked to the disease. Although the authors fully address this specific technology, they use what constitutes the seminal case of predictive genetic testing to analyze the adequacy of the existing regulatory framework. The authors conclude that the present regulatory system is inadequate and places a dangerous amount of reliance on primary care physicians. Their conclusion is grounded in the observation that most primary care physicians lack sufficient knowledge about this evolving investigative technology--which is highly subject to misinterpretation, and, though potentially helpful to some "high risk" patients, offers questionable clinical value for the general public. The authors set forth numerous proposals to promote both the quality and clinical value of predictive genetic testing so that it conforms to public health standards and can be properly integrated as a reliable component of medical care in specific situations.

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.

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

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.

A reconfigurable NAND/NOR genetic logic gate.

Science.gov (United States)

Goñi-Moreno, Angel; Amos, Martyn

2012-09-18

Engineering genetic Boolean logic circuits is a major research theme of synthetic biology. By altering or introducing connections between genetic components, novel regulatory networks are built in order to mimic the behaviour of electronic devices such as logic gates. While electronics is a highly standardized science, genetic logic is still in its infancy, with few agreed standards. In this paper we focus on the interpretation of logical values in terms of molecular concentrations. We describe the results of computational investigations of a novel circuit that is able to trigger specific differential responses depending on the input standard used. The circuit can therefore be dynamically reconfigured (without modification) to serve as both a NAND/NOR logic gate. This multi-functional behaviour is achieved by a) varying the meanings of inputs, and b) using branch predictions (as in computer science) to display a constrained output. A thorough computational study is performed, which provides valuable insights for the future laboratory validation. The simulations focus on both single-cell and population behaviours. The latter give particular insights into the spatial behaviour of our engineered cells on a surface with a non-homogeneous distribution of inputs. We present a dynamically-reconfigurable NAND/NOR genetic logic circuit that can be switched between modes of operation via a simple shift in input signal concentration. The circuit addresses important issues in genetic logic that will have significance for more complex synthetic biology applications.

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.

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.

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

Prefrontal gray matter volume mediates genetic risks for obesity.

Science.gov (United States)

Opel, N; Redlich, R; Kaehler, C; Grotegerd, D; Dohm, K; Heindel, W; Kugel, H; Thalamuthu, A; Koutsouleris, N; Arolt, V; Teuber, A; Wersching, H; Baune, B T; Berger, K; Dannlowski, U

2017-05-01

Genetic and neuroimaging research has identified neurobiological correlates of obesity. However, evidence for an integrated model of genetic risk and brain structural alterations in the pathophysiology of obesity is still absent. Here we investigated the relationship between polygenic risk for obesity, gray matter structure and body mass index (BMI) by the use of univariate and multivariate analyses in two large, independent cohorts (n=330 and n=347). Higher BMI and higher polygenic risk for obesity were significantly associated with medial prefrontal gray matter decrease, and prefrontal gray matter was further shown to significantly mediate the effect of polygenic risk for obesity on BMI in both samples. Building on this, the successful individualized prediction of BMI by means of multivariate pattern classification algorithms trained on whole-brain imaging data and external validations in the second cohort points to potential clinical applications of this imaging trait marker.

Genetic factors affecting statin concentrations and subsequent myopathy: a HuGENet systematic review

Science.gov (United States)

Canestaro, William J.; Austin, Melissa A.; Thummel, Kenneth E.

2015-01-01

Statins, 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase inhibitors, have proven efficacy in both lowering low-density-lipoprotein levels and preventing major coronary events, making them one of the most commonly prescribed drugs in the United States. Statins exhibit a class-wide side effect of muscle toxicity and weakness, which has led regulators to impose both dosage limitations and a recall. This review focuses on the best-characterized genetic factors associated with increased statin muscle concentrations, including the genes encoding cytochrome P450 enzymes (CYP2D6, CYP3A4, and CYP3A5), a mitochondrial enzyme (GATM), an influx transporter (SLCO1B1), and efflux transporters (ABCB1 and ABCG2). A systematic literature review was conducted to identify relevant research evaluating the significance of genetic variants predictive of altered statin concentrations and subsequent statin-related myopathy. Studies eligible for inclusion must have incorporated genotype information and must have associated it with some measure of myopathy, either creatine kinase levels or self-reported muscle aches and pains. After an initial review, focus was placed on seven genes that were adequately characterized to provide a substantive review: CYP2D6, CYP3A4, CYP3A5, GATM, SLCO1B1, ABCB1, and ABCG2. All statins were included in this review. Among the genetic factors evaluated, statin-related myopathy appears to be most strongly associated with variants in SLCO1B1. PMID:24810685

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

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

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

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.

Sir RA Fisher and the Evolution of Genetics

Indian Academy of Sciences (India)

quantitative genetics, a body of work that provides the conceptual underpinnings ... worked extensively with mutations that had large effects on structural ... altering the genetic composition of populations during adaptive ... exercise in ' writing.

Genetic Mutations in Cancer

Science.gov (United States)

Many different types of genetic mutations are found in cancer cells. This infographic outlines certain types of alterations that are present in cancer, such as missense, nonsense, frameshift, and chromosome rearrangements.

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.

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

Phosphorylation states of cell cycle and DNA repair proteins can be altered by the nsSNPs

International Nuclear Information System (INIS)

Savas, Sevtap; Ozcelik, Hilmi

2005-01-01

Phosphorylation is a reversible post-translational modification that affects the intrinsic properties of proteins, such as structure and function. Non-synonymous single nucleotide polymorphisms (nsSNPs) result in the substitution of the encoded amino acids and thus are likely to alter the phosphorylation motifs in the proteins. In this study, we used the web-based NetPhos tool to predict candidate nsSNPs that either introduce or remove putative phosphorylation sites in proteins that act in DNA repair and cell cycle pathways. Our results demonstrated that a total of 15 nsSNPs (16.9%) were likely to alter the putative phosphorylation patterns of 14 proteins. Three of these SNPs (CDKN1A-S31R, OGG1-S326C, and XRCC3-T241M) have already found to be associated with altered cancer risk. We believe that this set of nsSNPs constitutes an excellent resource for further molecular and genetic analyses. The novel systematic approach used in this study will accelerate the understanding of how naturally occurring human SNPs may alter protein function through the modification of phosphorylation mechanisms and contribute to disease susceptibility

Overexpression of AtLOV1 in Switchgrass alters plant architecture, lignin content, and flowering time.

Directory of Open Access Journals (Sweden)

Bin Xu

Full Text Available BACKGROUND: Switchgrass (Panicum virgatum L. is a prime candidate crop for biofuel feedstock production in the United States. As it is a self-incompatible polyploid perennial species, breeding elite and stable switchgrass cultivars with traditional breeding methods is very challenging. Translational genomics may contribute significantly to the genetic improvement of switchgrass, especially for the incorporation of elite traits that are absent in natural switchgrass populations. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we constitutively expressed an Arabidopsis NAC transcriptional factor gene, LONG VEGETATIVE PHASE ONE (AtLOV1, in switchgrass. Overexpression of AtLOV1 in switchgrass caused the plants to have a smaller leaf angle by changing the morphology and organization of epidermal cells in the leaf collar region. Also, overexpression of AtLOV1 altered the lignin content and the monolignol composition of cell walls, and caused delayed flowering time. Global gene-expression analysis of the transgenic plants revealed an array of responding genes with predicted functions in plant development, cell wall biosynthesis, and flowering. CONCLUSIONS/SIGNIFICANCE: To our knowledge, this is the first report of a single ectopically expressed transcription factor altering the leaf angle, cell wall composition, and flowering time of switchgrass, therefore demonstrating the potential advantage of translational genomics for the genetic improvement of this crop.

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.

Unique genetic loci identified for emotional behavior in control and chronic stress conditions.

Directory of Open Access Journals (Sweden)

Kimberly AK Carhuatanta

2014-10-01

Full Text Available An individual’s genetic background affects their emotional behavior and response to stress. Although studies have been conducted to identify genetic predictors for emotional behavior or stress response, it remains unknown how prior stress history alters the interaction between an individual’s genome and their emotional behavior. Therefore, the purpose of this study is to identify chromosomal regions that affect emotional behavior and are sensitive to stress exposure. We utilized the BXD behavioral genetics mouse model to identify chromosomal regions that predict fear learning and emotional behavior following exposure to a control or chronic stress environment. 62 BXD recombinant inbred strains and C57BL/6 and DBA/2 parental strains underwent behavioral testing including a classical fear conditioning paradigm and the elevated plus maze. Distinct quantitative trait loci (QTLs were identified for emotional learning, anxiety and locomotion in control and chronic stress populations. Candidate genes, including those with already known functions in learning and stress were found to reside within the identified QTLs. Our data suggest that chronic stress history reveals novel genetic predictors of emotional behavior.

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.

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.

Wetlands explain most in the genetic divergence pattern of Oncomelania hupensis.

Science.gov (United States)

Liang, Lu; Liu, Yang; Liao, Jishan; Gong, Peng

2014-10-01

Understanding the divergence patterns of hosts could shed lights on the prediction of their parasite transmission. No effort has been devoted to understand the drivers of genetic divergence pattern of Oncomelania hupensis, the only intermediate host of Schistosoma japonicum. Based on a compilation of two O. hupensis gene datasets covering a wide geographic range in China and an array of geographical distance and environmental dissimilarity metrics built from earth observation data and ecological niche modeling, we conducted causal modeling analysis via simple, partial Mantel test and local polynomial fitting to understand the interactions among isolation-by-distance, isolation-by-environment, and genetic divergence. We found that geography contributes more to genetic divergence than environmental isolation, and among all variables involved, wetland showed the strongest correlation with the genetic pairwise distances. These results suggested that in China, O. hupensis dispersal is strongly linked to the distribution of wetlands, and the current divergence pattern of both O. hupensis and schistosomiasis might be altered due to the changed wetland pattern with the accomplishment of the Three Gorges Dam and the South-to-North water transfer project. Copyright © 2014 Elsevier B.V. All rights reserved.

Prediction of Adult Dyslipidemia Using Genetic and Childhood Clinical Risk Factors: The Cardiovascular Risk in Young Finns Study.

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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.

Genetic alterations affecting cholesterol metabolism and human fertility.

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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.

Optimization the Initial Weights of Artificial Neural Networks via Genetic Algorithm Applied to Hip Bone Fracture Prediction

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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.

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

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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.

A systematic review of the factors associated with interest in predictive genetic testing for obesity, type II diabetes and heart disease.

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Collins, J; Ryan, L; Truby, H

2014-10-01

In the future, it may be possible for individuals to take a genetic test to determine their genetic predisposition towards developing lifestyle-related chronic diseases. A systematic review of the literature was undertaken to identify the factors associated with an interest in having predictive genetic testing for obesity, type II diabetes and heart disease amongst unaffected adults. Ovid Medline, PsycINFO and EMBASE online databases were searched using predefined search terms. Publications meeting the inclusion criteria (English language, free-living adult population not selected as a result of their disease diagnosis, reporting interest as an outcome, not related to a single gene inherited disease) were assessed for quality and content. Narrative synthesis of the results was undertaken. From the 2329 publications retrieved, eight studies met the inclusion criteria and were included in the review. Overall, the evidence base was small but of positive quality. Interest was associated with personal attitudes towards disease risk and the provision of information about genetic testing, shaped by perceived risk of disease and expected outcomes of testing. The role of demographic factors was investigated with largely inconclusive findings. Interest in predictive genetic testing for obesity, type II diabetes or heart disease was greatest amongst those who perceived the risk of disease to be high and/or the outcomes of testing to be beneficial. © 2013 The British Dietetic Association Ltd.

Prediction of warfarin maintenance dose in Han Chinese patients using a mechanistic model based on genetic and non-genetic factors.

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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

Resource allocation for maximizing prediction accuracy and genetic gain of genomic selection in plant breeding: a simulation experiment.

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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

Alteration of polymorphic systems of Centaurea scabiosa L. under chronic irradiation

International Nuclear Information System (INIS)

Lysenko, E.A.; Kal'chenko, V.A.; Shevchenko, V.A.; Lysenko, E.A.

1999-01-01

Isoenzyme and morphological polymorphism alteration in populations of perennial grass Centaurea scabiosa L. (scaly cornflower) has been studied. These populations exist on the territory of East Urals Radioactive Trace more than 40 years and are chronically exposed to β-radiation. Directional shift of allele frequencies on the loci Per 1 , Pgi 2 , Sod 1 , Lap has been detected. Fact of accumulating genetic load by chronically irradiated populations has been demonstrated. Possible reasons of discovered alterations are discussed. Analysis of the obtained data shows that the irradiation populations have greater similarity with one another than with a control, but relation between genetic distances and accumulated doses has not been revealed. Hypothesis is that an extra factor - gene flow from a clean territory influences the genetic structure of irradiated populations [ru

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

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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.

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.

Molecular genetic markers for thyroid FNAB. Established assays and future perspective.

Science.gov (United States)

Musholt, Thomas J; Musholt, P B

2015-01-01

Thyroid nodules > 1 cm are observed in about 12% of unselected adult employees aged 18-65 years screened by ultrasound scan (40). While intensive ultrasound screening leads to early detection of thyroid diseases, the determination of benign or malignant behaviour remains uncertain and may trigger anxieties in many patients and their physicians. A considerable number of thyroid resections are consecutively performed due to suspicion of malignancy in the detected nodes. Fine needle aspiration biopsy (FNAB) has been recommended for the assessment of thyroid nodules to facilitate detection of thyroid carcinomas but also to rule out malignancy and thereby avoid unnecessary thyroid resections. However, cytology results are dependent on experience of the respective cytologist and unfortunately inconclusive in many cases. Molecular genetic markers are already used nowadays to enhance sensitivity and specificity of FNAB cytology in some centers in Germany. The most clinically relevant molecular genetic markers as pre-operative diagnostic tools and the clinical implications for the intraoperative and postoperative management were reviewed. Molecular genetic markers predominantly focus on the preoperative detection of thyroid malignancies rather than the exclusion of thyroid carcinomas. While some centers routinely assess FNABs, other centers concentrate on FNABs with cytology results of follicular neoplasia or suspicion of thyroid carcinoma. Predominantly mutations of BRAF, RET/PTC, RAS, and PAX8/PPARγ or expression of miRNAs are analyzed. However, only the detection of BRAF mutations predicts the presence of (papillary) thyroid malignancy with almost 98% probability, indicating necessity of oncologic thyroid resections irrespective of the cytology result. Other genetic alterations are associated with thyroid malignancy with varying frequency and achieve less impact on the clinical management. Molecular genetic analysis of FNABs is increasingly performed in Germany

Journal of Genetics | Indian Academy of Sciences

Indian Academy of Sciences (India)

Home; Journals; Journal of Genetics. MD. SAIMUL ISLAM. Articles written in Journal of Genetics. Volume 95 Issue 3 September 2016 pp 551-563 RESEARCH ARTICLE. Frequent alterations of SLIT2–ROBO1–CDC42 signalling pathway in breast cancer: clinicopathological correlation · RITTWIKA BHATTACHARYA NUPUR ...

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

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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.

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

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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.

The genetic basis of addictive disorders.

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Ducci, Francesca; Goldman, David

2012-06-01

Addictions are common, chronic, and relapsing diseases that develop through a multistep process. The impact of addictions on morbidity and mortality is high worldwide. Twin studies have shown that the heritability of addictions ranges from 0.39 (hallucinogens) to 0.72 (cocaine). Twin studies indicate that genes influence each stage from initiation to addiction, although the genetic determinants may differ. Addictions are by definition the result of gene × environment interaction. These disorders, which are in part volitional, in part inborn, and in part determined by environmental experience, pose the full range of medical, genetic, policy, and moral challenges. Gene discovery is being facilitated by a variety of powerful approaches, but is in its infancy. It is not surprising that the genes discovered so far act in a variety of ways: via altered metabolism of drug (the alcohol and nicotine metabolic gene variants), via altered function of a drug receptor (the nicotinic receptor, which may alter affinity for nicotine but as discussed may also alter circuitry of reward), and via general mechanisms of addiction (genes such as monoamine oxidase A and the serotonin transporter that modulate stress response, emotion, and behavioral control). Addiction medicine today benefits from genetic studies that buttress the case for a neurobiologic origin of addictive behavior, and some general information on familially transmitted propensity that can be used to guide prevention. A few well-validated, specific predictors such as OPRM1, ADH1B, ALDH2, CHRNA5, and CYP26 have been identified and can provide some specific guidance, for example, to understand alcohol-related flushing and upper GI cancer risk (ADH1B and AKLDH2), variation in nicotine metabolism (CYP26), and, potentially, naltrexone treatment response (OPRM1). However, the genetic predictors available are few in number and account for only a small portion of the genetic variance in liability, and have not been integrated

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

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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.

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.

Predicting recurrent aphthous ulceration using genetic algorithms-optimized neural networks

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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

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

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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.

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

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.

Genetic structure and genetic diversity of Swietenia macrophylla in areas subjected to selective logging in Quintana Roo, Mexico

OpenAIRE

Alcalá, Raúl Ernesto; Cruz, Silvia De la; Gutiérrez-Granados, Gabriel

2015-01-01

The hypothesis that selective logging has a negative effect by altering the genetic parameters of tropical tree species was evaluated. The genetic diversity and genetic structure between adult trees (N = 47) and saplings (N = 50) of Swietenia macrophylla were contrasted within an area subjected to selective logging in the Mayan zone. Although differences in the number of alleles and in their frequencies were detected between both groups, the observed and expected heterozygosity and the coeffi...

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.

Genetic parameters of blood β-hydroxybutyrate predicted from milk infrared spectra and clinical ketosis, and their associations with milk production traits in Norwegian Red cows.

Science.gov (United States)

Belay, T K; Svendsen, M; Kowalski, Z M; Ådnøy, T

2017-08-01

The aim of this study was to estimate genetic parameters for blood β-hydroxybutyrate (BHB) predicted from milk spectra and for clinical ketosis (KET), and to examine genetic association of blood BHB with KET and milk production traits (milk, fat, protein, and lactose yields, and milk fat, protein, and lactose contents). Data on milk traits, KET, and milk spectra were obtained from the Norwegian Dairy Herd Recording System with legal permission from TINE SA (Ås, Norway), the Norwegian Dairy Association that manages the central database. Data recorded up to 120 d after calving were considered. Blood BHB was predicted from milk spectra using a calibration model developed based on milk spectra and blood BHB measured in Polish dairy cows. The predicted blood BHB was grouped based on days in milk into 4 groups and each group was considered as a trait. The milk components for test-day milk samples were obtained by Fourier transform mid-infrared spectrometer with previously developed calibration equations from Foss (Hillerød, Denmark). Veterinarian-recorded KET data within 15 d before calving to 120 d after calving were used. Data were analyzed using univariate or bivariate linear animal models. Heritability estimates for predicted blood BHB at different stages of lactation were moderate, ranging from 0.250 to 0.365. Heritability estimate for KET from univariate analysis was 0.078, and the corresponding average estimate from bivariate analysis with BHB or milk production traits was 0.002. Genetic correlations between BHB traits were higher for adjacent lactation intervals and decreased as intervals were further apart. Predicted blood BHB at first test day was moderately genetically correlated with KET (0.469) and milk traits (ranged from -0.367 with protein content to 0.277 with milk yield), except for milk fat content from across lactation stages that had near zero genetic correlation with BHB (0.033). These genetic correlations indicate that a lower BHB is genetically

Patterns of somatic alterations between matched primary and metastatic colorectal tumors characterized by whole-genome sequencing.

Science.gov (United States)

Xie, Tao; Cho, Yong Beom; Wang, Kai; Huang, Donghui; Hong, Hye Kyung; Choi, Yoon-La; Ko, Young Hyeh; Nam, Do-Hyun; Jin, Juyoun; Yang, Heekyoung; Fernandez, Julio; Deng, Shibing; Rejto, Paul A; Lee, Woo Yong; Mao, Mao

2014-10-01

Colorectal cancer (CRC) patients have poor prognosis after formation of distant metastasis. Understanding the molecular mechanisms by which genetic changes facilitate metastasis is critical for the development of targeted therapeutic strategies aimed at controlling disease progression while minimizing toxic side effects. A comprehensive portrait of somatic alterations in CRC and the changes between primary and metastatic tumors has yet to be developed. We performed whole genome sequencing of two primary CRC tumors and their matched liver metastases. By comparing to matched germline DNA, we catalogued somatic alterations at multiple scales, including single nucleotide variations, small insertions and deletions, copy number aberrations and structural variations in both the primary and matched metastasis. We found that the majority of these somatic alterations are present in both sites. Despite the overall similarity, several de novo alterations in the metastases were predicted to be deleterious, in genes including FBXW7, DCLK1 and FAT2, which might contribute to the initiation and progression of distant metastasis. Through careful examination of the mutation prevalence among tumor cells at each site, we also proposed distinct clonal evolution patterns between primary and metastatic tumors in the two cases. These results suggest that somatic alterations may play an important role in driving the development of colorectal cancer metastasis and present challenges and opportunities when considering the choice of treatment. Copyright © 2014 Elsevier Inc. All rights reserved.

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.

Genet-specific spawning patterns in Acropora palmata

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Miller, M. W.; Williams, D. E.; Fisch, J.

2016-12-01

The broadcast spawning elkhorn coral, Acropora palmata, requires outcrossing among different genets for effective fertilization. Hence, a low density of genets in parts of its range emphasizes the need for precise synchrony among neighboring genets as sperm concentration dilutes rapidly in open-ocean conditions. We documented the genet-specific nightly occurrence of spawning of A. palmata over 8 yr in a depauperate population in the Florida Keys to better understand this potential reproductive hurdle. The observed population failed to spawn within the predicted monthly window (nights 2-6 after the full moon in August) in three of the 8 yr of observation; negligible spawning was observed in a fourth year. Moreover, genet-specific patterns are evident in that (1) certain genets have significantly greater odds of spawning overall and (2) certain genets predictably spawn on the earlier and others on the later lunar nights within the predicted window. Given the already low genet density in this population, this pattern implies a substantial degree of wasted reproductive effort and supports the hypothesis that depensatory factors are impairing recovery in this species.

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.

The relative abundance of predicted genes associated with ammonia-oxidation, nitrate reduction, and biomass decomposition in mineral soil are altered by intensive timber harvest.

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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

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

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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.

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...

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

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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.

Genetic markers as a predictive tool based on statistics in medical practice: ethical considerations through the analysis of the use of HLA-B27 in rheumatology in France

Directory of Open Access Journals (Sweden)

Hélène eColineaux

2015-10-01

Full Text Available INTRODUCTION. The use of genetic predictive markers in medical practice does not necessarily bear the same kind of medical and ethical consequences than that of genes directly involved in monogenic diseases. However, the French bioethics law framed in the same way the production and use of any genetic information. It seems therefore necessary to explore the practical and ethical context of the actual use of predictive markers in order to highlight their specific stakes. In this study, we document the uses of HLA-B*27, which are an interesting example of the multiple features of genetic predictive marker in general medical practice.MATERIAL & METHODS. The aims of this monocentric and qualitative study were to identify concrete and ethical issues of using the HLA-B*27 marker and the interests and limits of the legal framework as perceived by prescribers. In this regard, a thematic and descriptive analysis of five rheumatologists’ semi-structured and face-to-face interviews was performed.RESULTS. According to most of the interviewees, HLA-B*27 is an overframed test because they considered that this test is not really genetic or at least does not have the same nature as classical genetic tests; HLA-B*27 is not concerned by the ethical challenges of genetic test; the major ethics stake of this marker is not linked to its genetic nature but rather to the complexity of the probabilistic information. This study allows also showing that HLA-B*27, validated for a certain usage, may be used in different ways in practice.DISCUSSION. This marker and its clinical uses underline the challenges of translating both statistical concepts and unifying legal framework in clinical practice. This study allows identifying some new aspects and stakes of genetics in medicine and shows the need of additional studies about the use of predictive genetic markers, in order to provide a better basis for decisions and legal framework regarding these practices.

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

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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

m6ASNP: a tool for annotating genetic variants by m6A function.

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Jiang, Shuai; Xie, Yubin; He, Zhihao; Zhang, Ya; Zhao, Yuli; Chen, Li; Zheng, Yueyuan; Miao, Yanyan; Zuo, Zhixiang; Ren, Jian

2018-04-02

Large-scale genome sequencing projects have identified many genetic variants for diverse diseases. A major goal of these projects is to characterize these genetic variants to provide insight into their function and roles in diseases. N6-methyladenosine (m6A) is one of the most abundant RNA modifications in eukaryotes. Recent studies have revealed that aberrant m6A modifications are involved in many diseases. In this study, we present a user-friendly web server called "m6ASNP" that is dedicated to the identification of genetic variants targeting m6A modification sites. A random forest model was implemented in m6ASNP to predict whether the methylation status of a m6A site is altered by the variants surrounding the site. In m6ASNP, genetic variants in a standard VCF format are accepted as the input data, and the output includes an interactive table containing the genetic variants annotated by m6A function. In addition, statistical diagrams and a genome browser are provided to visualize the characteristics and annotate the genetic variants. We believe that m6ASNP is a highly convenient tool that can be used to boost further functional studies investigating genetic variants. The web server "m6ASNP" is implemented in JAVA and PHP and is freely available at http://m6asnp.renlab.org.

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

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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.

The ecological imperative and its application to ethical issues in human genetic technology

OpenAIRE

W. Malcolm Byrnes

2003-01-01

As a species, we are on the cusp of being able to alter that which makes us uniquely human, our genome. Two new genetic technologies, embryo selection and germline engineering, are either in use today or may be developed in the future. Embryo selection acts to alter the human gene pool, reducing genetic diversity, while germline engineering will have the ability to alter directly the genomes of engineered individuals. Our genome has come to be what it is through an evolutionary process extend...

Biopsychosocial influence on exercise-induced injury: genetic and psychological combinations are predictive of shoulder pain phenotypes.

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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

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

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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.

Identification of the genetic and clinical characteristics of neuroblastomas using genome-wide analysis.

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Uryu, Kumiko; Nishimura, Riki; Kataoka, Keisuke; Sato, Yusuke; Nakazawa, Atsuko; Suzuki, Hiromichi; Yoshida, Kenichi; Seki, Masafumi; Hiwatari, Mitsuteru; Isobe, Tomoya; Shiraishi, Yuichi; Chiba, Kenichi; Tanaka, Hiroko; Miyano, Satoru; Koh, Katsuyoshi; Hanada, Ryoji; Oka, Akira; Hayashi, Yasuhide; Ohira, Miki; Kamijo, Takehiko; Nagase, Hiroki; Takimoto, Tetsuya; Tajiri, Tatsuro; Nakagawara, Akira; Ogawa, Seishi; Takita, Junko

2017-12-08

To provide better insight into the genetic signatures of neuroblastomas, we analyzed 500 neuroblastomas (included specimens from JNBSG) using targeted-deep sequencing for 10 neuroblastoma-related genes and SNP arrays analysis. ALK expression was evaluated using immunohistochemical analysis in 259 samples. Based on genetic alterations, the following 6 subgroups were identified: groups A ( ALK abnormalities), B (other gene mutations), C ( MYCN amplification), D (11q loss of heterozygosity [LOH]), E (at least 1 copy number variants), and F (no genetic changes). Groups A to D showed advanced disease and poor prognosis, whereas groups E and F showed excellent prognosis. Intriguingly, in group A, MYCN amplification was not a significant prognostic marker, while high ALK expression was a relevant indicator for prognosis ( P = 0.033). Notably, the co-existence of MYCN amplification and 1p LOH, and the co-deletion of 3p and 11q were significant predictors of relapse ( P = 0.043 and P = 0.040). Additionally, 6q/8p LOH and 17q gain were promising indicators of survival in patients older than 5 years, and 1p, 4p, and 11q LOH potentially contributed to outcome prediction in the intermediate-risk group. Our genetic overview clarifies the clinical impact of genetic signatures and aids in the better understanding of genetic basis of neuroblastoma.

Genetic testing in the epilepsies—Report of the ILAE Genetics Commission

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Ottman, Ruth; Hirose, Shinichi; Jain, Satish; Lerche, Holger; Lopes-Cendes, Iscia; Noebels, Jeffrey L.; Serratosa, José; Zara, Federico; Scheffer, Ingrid E.

2010-01-01

SUMMARY In this report, the International League Against Epilepsy (ILAE) Genetics Commission discusses essential issues to be considered with regard to clinical genetic testing in the epilepsies. Genetic research on the epilepsies has led to the identification of more than 20 genes with a major effect on susceptibility to idiopathic epilepsies. The most important potential clinical application of these discoveries is genetic testing: the use of genetic information, either to clarify the diagnosis in people already known or suspected to have epilepsy (diagnostic testing), or to predict onset of epilepsy in people at risk because of a family history (predictive testing). Although genetic testing has many potential benefits, it also has potential harms, and assessment of these potential benefits and harms in particular situations is complex. Moreover, many treating clinicians are unfamiliar with the types of tests available, how to access them, how to decide whether they should be offered, and what measures should be used to maximize benefit and minimize harm to their patients. Because the field is moving rapidly, with new information emerging practically every day, we present a framework for considering the clinical utility of genetic testing that can be applied to many different syndromes and clinical contexts. Given the current state of knowledge, genetic testing has high0020clinical utility in few clinical contexts, but in some of these it carries implications for daily clinical practice. PMID:20100225

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

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

The landscape of genomic alterations across childhood cancers

DEFF Research Database (Denmark)

Gröbner, Susanne N; Worst, Barbara C; Weischenfeldt, Joachim

2018-01-01

Pan-cancer analyses that examine commonalities and differences among various cancer types have emerged as a powerful way to obtain novel insights into cancer biology. Here we present a comprehensive analysis of genetic alterations in a pan-cancer cohort including 961 tumours from children, adoles...

Eco-genetic modeling of contemporary life-history evolution.

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Dunlop, Erin S; Heino, Mikko; Dieckmann, Ulf

2009-10-01

We present eco-genetic modeling as a flexible tool for exploring the course and rates of multi-trait life-history evolution in natural populations. We build on existing modeling approaches by combining features that facilitate studying the ecological and evolutionary dynamics of realistically structured populations. In particular, the joint consideration of age and size structure enables the analysis of phenotypically plastic populations with more than a single growth trajectory, and ecological feedback is readily included in the form of density dependence and frequency dependence. Stochasticity and life-history trade-offs can also be implemented. Critically, eco-genetic models permit the incorporation of salient genetic detail such as a population's genetic variances and covariances and the corresponding heritabilities, as well as the probabilistic inheritance and phenotypic expression of quantitative traits. These inclusions are crucial for predicting rates of evolutionary change on both contemporary and longer timescales. An eco-genetic model can be tightly coupled with empirical data and therefore may have considerable practical relevance, in terms of generating testable predictions and evaluating alternative management measures. To illustrate the utility of these models, we present as an example an eco-genetic model used to study harvest-induced evolution of multiple traits in Atlantic cod. The predictions of our model (most notably that harvesting induces a genetic reduction in age and size at maturation, an increase or decrease in growth capacity depending on the minimum-length limit, and an increase in reproductive investment) are corroborated by patterns observed in wild populations. The predicted genetic changes occur together with plastic changes that could phenotypically mask the former. Importantly, our analysis predicts that evolutionary changes show little signs of reversal following a harvest moratorium. This illustrates how predictions offered by

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.

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.

Clerics urge ban on altering germline cells.

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Norman, C

1983-06-24

A resolution calling for a ban on genetic engineering of human reproductive cells has been signed by leaders of almost every major church group in the United States. Some of the religious leaders, while not certain that a total moratorium should be placed on altering germline cells, signed the statement in order to stimulate public debate on the issue. Legislation has recently been introduced in Congress to set up a committee to monitor genetic engineering and its human applications, but author Jeremy Rifkin, the impetus behind the church leaders' resolution, argues that such tampering threatens the gene pool and should be banned altogether.

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

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

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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.

The Effect of Recurrent Floods on Genetic Composition of Marble Trout Populations

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Pujolar, José Martin; Vincenzi, Simone; Zane, Lorenzo; Jesensek, Dusan; De Leo, Giulio A.; Crivelli, Alain J.

2011-01-01

A changing global climate can threaten the diversity of species and ecosystems. We explore the consequences of catastrophic disturbances in determining the evolutionary and demographic histories of secluded marble trout populations in Slovenian streams subjected to weather extremes, in particular recurrent flash floods and debris flows causing massive mortalities. Using microsatellite data, a pattern of extreme genetic differentiation was found among populations (global F ST of 0.716), which exceeds the highest values reported in freshwater fish. All locations showed low levels of genetic diversity as evidenced by low heterozygosities and a mean of only 2 alleles per locus, with few or no rare alleles. Many loci showed a discontinuous allele distribution, with missing alleles across the allele size range, suggestive of a population contraction. Accordingly, bottleneck episodes were inferred for all samples with a reduction in population size of 3–4 orders of magnitude. The reduced level of genetic diversity observed in all populations implies a strong impact of genetic drift, and suggests that along with limited gene flow, genetic differentiation might have been exacerbated by recurrent mortalities likely caused by flash flood and debris flows. Due to its low evolutionary potential the species might fail to cope with an intensification and altered frequency of flash flood events predicted to occur with climate change. PMID:21931617

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

76 FR 80869 - Monsanto Co.; Determination of Nonregulated Status of Corn Genetically Engineered for Drought...

Science.gov (United States)

2011-12-27

... and products altered or produced through genetic engineering that are plant pests or that there is... in 7 CFR part 340, ``Introduction of Organisms and Products Altered or Produced Through Genetic Engineering Which Are Plant Pests or Which There Is Reason to Believe Are Plant Pests,'' regulate, among other...

Alterations of the TP53 Gene in Gastric and Esophageal Carcinogenesis

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Marilanda Ferreira Bellini

2012-01-01

Full Text Available TP53 genes is one of more important tumor suppressor gene, which acts as a potent transcription factor with fundamental role in the maintenance of genetic stability. The development of esophageal and gastric cancers is a multistep process resulting in successive accumulation of genetic alterations that culminates in the malignant transformation. Thus, this study highlights the participation of the main genetic alterations of the TP53 gene in esophageal and gastric carcinogenesis. Among these changes, high frequency of TP53 mutations, loss of heterozygosity (LOH, overexpression of the p53 protein, and consequently loss of p53 function, which would be early events in esophageal and gastric cancers, as well as an important biomarker of the prognosis and treatment response. Furthermore, Single Nucleotide Polymorphisms (SNPs of TP53 have been implicated in the development and prognosis of several cancers, mainly TP53 codon 72 polymorphism whose role has been extensively studied in relation to susceptibility for esophageal and gastric cancer development.

Predicting Flowering Behavior and Exploring Its Genetic Determinism in an Apple Multi-family Population Based on Statistical Indices and Simplified Phenotyping.

Science.gov (United States)

Durand, Jean-Baptiste; Allard, Alix; Guitton, Baptiste; van de Weg, Eric; Bink, Marco C A M; Costes, Evelyne

2017-01-01

Irregular flowering over years is commonly observed in fruit trees. The early prediction of tree behavior is highly desirable in breeding programmes. This study aims at performing such predictions, combining simplified phenotyping and statistics methods. Sequences of vegetative vs. floral annual shoots (AS) were observed along axes in trees belonging to five apple related full-sib families. Sequences were analyzed using Markovian and linear mixed models including year and site effects. Indices of flowering irregularity, periodicity and synchronicity were estimated, at tree and axis scales. They were used to predict tree behavior and detect QTL with a Bayesian pedigree-based analysis, using an integrated genetic map containing 6,849 SNPs. The combination of a Biennial Bearing Index (BBI) with an autoregressive coefficient (γ g ) efficiently predicted and classified the genotype behaviors, despite few misclassifications. Four QTLs common to BBIs and γ g and one for synchronicity were highlighted and revealed the complex genetic architecture of the traits. Irregularity resulted from high AS synchronism, whereas regularity resulted from either asynchronous locally alternating or continual regular AS flowering. A relevant and time-saving method, based on a posteriori sampling of axes and statistical indices is proposed, which is efficient to evaluate the tree breeding values for flowering regularity and could be transferred to other species.

The molecular genetic makeup of acute lymphoblastic leukemia.

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Mullighan, Charles G

2012-01-01

Genomic profiling has transformed our understanding of the genetic basis of acute lymphoblastic leukemia (ALL). Recent years have seen a shift from microarray analysis and candidate gene sequencing to next-generation sequencing. Together, these approaches have shown that many ALL subtypes are characterized by constellations of structural rearrangements, submicroscopic DNA copy number alterations, and sequence mutations, several of which have clear implications for risk stratification and targeted therapeutic intervention. Mutations in genes regulating lymphoid development are a hallmark of ALL, and alterations of the lymphoid transcription factor gene IKZF1 (IKAROS) are associated with a high risk of treatment failure in B-ALL. Approximately 20% of B-ALL cases harbor genetic alterations that activate kinase signaling that may be amenable to treatment with tyrosine kinase inhibitors, including rearrangements of the cytokine receptor gene CRLF2; rearrangements of ABL1, JAK2, and PDGFRB; and mutations of JAK1 and JAK2. Whole-genome sequencing has also identified novel targets of mutation in aggressive T-lineage ALL, including hematopoietic regulators (ETV6 and RUNX1), tyrosine kinases, and epigenetic regulators. Challenges for the future are to comprehensively identify and experimentally validate all genetic alterations driving leukemogenesis and treatment failure in childhood and adult ALL and to implement genomic profiling into the clinical setting to guide risk stratification and targeted therapy.

Molecular and pro-inflammatory genetic profile in gastric carcinomas

NARCIS (Netherlands)

Sitarz, R.

2009-01-01

Gastric cancer is a result from the combination of environmental factors and an accumulation of specific genetic alterations, and affects mainly the older population. It is known that genetic factors play a more important role in early onset gastric cancers than in conventional gastric cancer

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.

Genetics in Relation to Biology.

Science.gov (United States)

Stewart, J. Bird

1987-01-01

Claims that most instruction dealing with genetics is limited to sex education and personal hygiene. Suggests that the biology curriculum should begin to deal with other issues related to genetics, including genetic normality, prenatal diagnoses, race, and intelligence. Predicts these topics will begin to appear in British examination programs.…

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.

Developing genetic epidemiological models to predict risk for nasopharyngeal carcinoma in high-risk population of China.

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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.

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

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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.

Integrated analysis of HPV-mediated immune alterations in cervical cancer.

Science.gov (United States)

Chen, Long; Luan, Shaohong; Xia, Baoguo; Liu, Yansheng; Gao, Yuan; Yu, Hongyan; Mu, Qingling; Zhang, Ping; Zhang, Weina; Zhang, Shengmiao; Wei, Guopeng; Yang, Min; Li, Ke

2018-05-01

Human papillomavirus (HPV) infection is the primary cause of cervical cancer. HPV-mediated immune alterations are known to play crucial roles in determining viral persistence and host cell transformation. We sought to thoroughly understand HPV-directed immune alterations in cervical cancer by exploring publically available datasets. 130 HPV positive and 7 HPV negative cervical cancer cases from The Cancer Genome Atlas were compared for differences in gene expression levels and functional enrichment. Analyses for copy number variation (CNV) and genetic mutation were conducted for differentially expressed immune genes. Kaplan-Meier analysis was performed to assess survival and relapse differences across cases with or without alterations of the identified immune signature genes. Genes up-regulated in HPV positive cervical cancer were enriched for various gene ontology terms of immune processes (P=1.05E-14~1.00E-05). Integrated analysis of the differentially expressed immune genes identified 9 genes that displayed either CNV, genetic mutation and/or gene expression changes in at least 10% of the cases of HPV positive cervical cancer. Genomic amplification may cause elevated levels of these genes in some HPV positive cases. Finally, patients with alterations in at least one of the nine signature genes overall had earlier relapse compared to those without any alterations. The altered expression of either TFRC or MMP13 may indicate poor survival for a subset of cervical cancer patients (P=1.07E-07). We identified a novel immune gene signature for HPV positive cervical cancer that is potentially associated with early relapse of cervical cancer. Copyright © 2018. Published by Elsevier Inc.

Innate Immune Signalling Genetics of Pain, Cognitive Dysfunction and Sickness Symptoms in Cancer Pain Patients Treated with Transdermal Fentanyl

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Barratt, Daniel T.; Klepstad, Pål; Dale, Ola; Kaasa, Stein; Somogyi, Andrew A.

2015-01-01

Common adverse symptoms of cancer and chemotherapy are a major health burden; chief among these is pain, with opioids including transdermal fentanyl the mainstay of treatment. Innate immune activation has been implicated generally in pain, opioid analgesia, cognitive dysfunction, and sickness type symptoms reported by cancer patients. We aimed to determine if genetic polymorphisms in neuroimmune activation pathways alter the serum fentanyl concentration-response relationships for pain control, cognitive dysfunction, and other adverse symptoms, in cancer pain patients. Cancer pain patients (468) receiving transdermal fentanyl were genotyped for 31 single nucleotide polymorphisms in 19 genes: CASP1, BDNF, CRP, LY96, IL6, IL1B, TGFB1, TNF, IL10, IL2, TLR2, TLR4, MYD88, IL6R, OPRM1, ARRB2, COMT, STAT6 and ABCB1. Lasso and backward stepwise generalised linear regression were used to identify non-genetic and genetic predictors, respectively, of pain control (average Brief Pain Inventory fentanyl concentrations did not predict between-patient variability in these outcomes, nor did genetic factors predict pain control, sickness response or opioid adverse event complaint. Carriers of the MYD88 rs6853 variant were half as likely to have cognitive dysfunction (11/111) than wild-type patients (69/325), with a relative risk of 0.45 (95% CI: 0.27 to 0.76) when accounting for major non-genetic predictors (age, Karnofsky functional score). This supports the involvement of innate immune signalling in cognitive dysfunction, and identifies MyD88 signalling pathways as a potential focus for predicting and reducing the burden of cognitive dysfunction in cancer pain patients. PMID:26332828

76 FR 63279 - Monsanto Co.; Determination of Nonregulated Status for Soybean Genetically Engineered for Insect...

Science.gov (United States)

2011-10-12

... and products altered or produced through genetic engineering that are plant pests or that there is... regulations in 7 CFR part 340, ``Introduction of Organisms and Products Altered or Produced Through Genetic Engineering Which Are Plant Pests or Which There Is Reason to Believe Are Plant Pests,'' regulate, among other...

Selection on Optimal Haploid Value Increases Genetic Gain and Preserves More Genetic Diversity Relative to Genomic Selection.

Science.gov (United States)

Daetwyler, Hans D; Hayden, Matthew J; Spangenberg, German C; Hayes, Ben J

2015-08-01

Doubled haploids are routinely created and phenotypically selected in plant breeding programs to accelerate the breeding cycle. Genomic selection, which makes use of both phenotypes and genotypes, has been shown to further improve genetic gain through prediction of performance before or without phenotypic characterization of novel germplasm. Additional opportunities exist to combine genomic prediction methods with the creation of doubled haploids. Here we propose an extension to genomic selection, optimal haploid value (OHV) selection, which predicts the best doubled haploid that can be produced from a segregating plant. This method focuses selection on the haplotype and optimizes the breeding program toward its end goal of generating an elite fixed line. We rigorously tested OHV selection breeding programs, using computer simulation, and show that it results in up to 0.6 standard deviations more genetic gain than genomic selection. At the same time, OHV selection preserved a substantially greater amount of genetic diversity in the population than genomic selection, which is important to achieve long-term genetic gain in breeding populations. Copyright © 2015 by the Genetics Society of America.

Genetic and linguistic coevolution in Northern Island Melanesia.

Science.gov (United States)

Hunley, Keith; Dunn, Michael; Lindström, Eva; Reesink, Ger; Terrill, Angela; Healy, Meghan E; Koki, George; Friedlaender, Françoise R; Friedlaender, Jonathan S

2008-10-01

Recent studies have detailed a remarkable degree of genetic and linguistic diversity in Northern Island Melanesia. Here we utilize that diversity to examine two models of genetic and linguistic coevolution. The first model predicts that genetic and linguistic correspondences formed following population splits and isolation at the time of early range expansions into the region. The second is analogous to the genetic model of isolation by distance, and it predicts that genetic and linguistic correspondences formed through continuing genetic and linguistic exchange between neighboring populations. We tested the predictions of the two models by comparing observed and simulated patterns of genetic variation, genetic and linguistic trees, and matrices of genetic, linguistic, and geographic distances. The data consist of 751 autosomal microsatellites and 108 structural linguistic features collected from 33 Northern Island Melanesian populations. The results of the tests indicate that linguistic and genetic exchange have erased any evidence of a splitting and isolation process that might have occurred early in the settlement history of the region. The correlation patterns are also inconsistent with the predictions of the isolation by distance coevolutionary process in the larger Northern Island Melanesian region, but there is strong evidence for the process in the rugged interior of the largest island in the region (New Britain). There we found some of the strongest recorded correlations between genetic, linguistic, and geographic distances. We also found that, throughout the region, linguistic features have generally been less likely to diffuse across population boundaries than genes. The results from our study, based on exceptionally fine-grained data, show that local genetic and linguistic exchange are likely to obscure evidence of the early history of a region, and that language barriers do not particularly hinder genetic exchange. In contrast, global patterns may

Genetic and linguistic coevolution in Northern Island Melanesia.

Directory of Open Access Journals (Sweden)

Keith Hunley

2008-10-01

Full Text Available Recent studies have detailed a remarkable degree of genetic and linguistic diversity in Northern Island Melanesia. Here we utilize that diversity to examine two models of genetic and linguistic coevolution. The first model predicts that genetic and linguistic correspondences formed following population splits and isolation at the time of early range expansions into the region. The second is analogous to the genetic model of isolation by distance, and it predicts that genetic and linguistic correspondences formed through continuing genetic and linguistic exchange between neighboring populations. We tested the predictions of the two models by comparing observed and simulated patterns of genetic variation, genetic and linguistic trees, and matrices of genetic, linguistic, and geographic distances. The data consist of 751 autosomal microsatellites and 108 structural linguistic features collected from 33 Northern Island Melanesian populations. The results of the tests indicate that linguistic and genetic exchange have erased any evidence of a splitting and isolation process that might have occurred early in the settlement history of the region. The correlation patterns are also inconsistent with the predictions of the isolation by distance coevolutionary process in the larger Northern Island Melanesian region, but there is strong evidence for the process in the rugged interior of the largest island in the region (New Britain. There we found some of the strongest recorded correlations between genetic, linguistic, and geographic distances. We also found that, throughout the region, linguistic features have generally been less likely to diffuse across population boundaries than genes. The results from our study, based on exceptionally fine-grained data, show that local genetic and linguistic exchange are likely to obscure evidence of the early history of a region, and that language barriers do not particularly hinder genetic exchange. In contrast

Use of biological priors enhances understanding of genetic architecture and genomic prediction of complex traits within and between dairy cattle breeds.

Science.gov (United States)

Fang, Lingzhao; Sahana, Goutam; Ma, Peipei; Su, Guosheng; Yu, Ying; Zhang, Shengli; Lund, Mogens Sandø; Sørensen, Peter

2017-08-10

A better understanding of the genetic architecture underlying complex traits (e.g., the distribution of causal variants and their effects) may aid in the genomic prediction. Here, we hypothesized that the genomic variants of complex traits might be enriched in a subset of genomic regions defined by genes grouped on the basis of "Gene Ontology" (GO), and that incorporating this independent biological information into genomic prediction models might improve their predictive ability. Four complex traits (i.e., milk, fat and protein yields, and mastitis) together with imputed sequence variants in Holstein (HOL) and Jersey (JER) cattle were analysed. We first carried out a post-GWAS analysis in a HOL training population to assess the degree of enrichment of the association signals in the gene regions defined by each GO term. We then extended the genomic best linear unbiased prediction model (GBLUP) to a genomic feature BLUP (GFBLUP) model, including an additional genomic effect quantifying the joint effect of a group of variants located in a genomic feature. The GBLUP model using a single random effect assumes that all genomic variants contribute to the genomic relationship equally, whereas GFBLUP attributes different weights to the individual genomic relationships in the prediction equation based on the estimated genomic parameters. Our results demonstrate that the immune-relevant GO terms were more associated with mastitis than milk production, and several biologically meaningful GO terms improved the prediction accuracy with GFBLUP for the four traits, as compared with GBLUP. The improvement of the genomic prediction between breeds (the average increase across the four traits was 0.161) was more apparent than that it was within the HOL (the average increase across the four traits was 0.020). Our genomic feature modelling approaches provide a framework to simultaneously explore the genetic architecture and genomic prediction of complex traits by taking advantage of

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.

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

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

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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

Medulloblastoma: Molecular Genetics and Animal Models

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Corey Raffel

2004-07-01

Full Text Available Medulloblastoma is a primary brain tumor found in the cerebellum of children. The tumor occurs in association with two inherited cancer syndromes: Turcot syndrome and Gorlin syndrome. Insights into the molecular biology of the tumor have come from looking at alterations in the genes altered in these syndromes, PTC and APC, respectively. Murine models of medulloblastoma have been constructed based on these alterations. Additional murine models that, while mimicking the appearance of the human tumor, seem unrelated to the human tumor's molecular alterations have been made. In this review, the clinical picture, origin, molecular biology, murine models of medulloblastoma are discussed. Although a great deal has been discovered about this tumor, the genetic alterations responsible for tumor development in a majority of patients have yet to be described.

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

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

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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.

On the relation between gene flow theory and genetic gain

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Woolliams John A

2000-01-01

Full Text Available Abstract In conventional gene flow theory the rate of genetic gain is calculated as the summed products of genetic selection differential and asymptotic proportion of genes deriving from sex-age groups. Recent studies have shown that asymptotic proportions of genes predicted from conventional gene flow theory may deviate considerably from true proportions. However, the rate of genetic gain predicted from conventional gene flow theory was accurate. The current note shows that the connection between asymptotic proportions of genes and rate of genetic gain that is embodied in conventional gene flow theory is invalid, even though genetic gain may be predicted correctly from it.

[Diabetes and predictive medicine--parallax of the present time].

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Rybka, J

2010-04-01

Predictive genetics uses genetic testing to estimate the risk in asymptomatic persons. Since in the case of multifactorial diseases predictive genetic analysis deals with findings which allow wider interpretation, it has a higher predictive value in expressly qualified diseases (monogenous) with high penetration compared to multifactorial (polygenous) diseases with high participation of environmental factors. In most "civilisation" (multifactorial) diseases including diabetes, heredity and environmental factors do not play two separate, independent roles. Instead, their interactions play a principal role. The new classification of diabetes is based on the implementation of not only ethiopathogenetic, but also genetic research. Diabetes mellitus type 1 (DM1T) is a polygenous multifactorial disease with the genetic component carrying about one half of the risk, the non-genetic one the other half. The study of the autoimmune nature of DM1T in connection with genetic analysis is going to bring about new insights in DM1T prediction. The author presents new pieces of knowledge on molecular genetics concerning certain specific types of diabetes. Issues relating to heredity in diabetes mellitus type 2 (DM2T) are even more complex. The disease has a polygenous nature, and the phenotype of a patient with DM2T, in addition to environmental factors, involves at least three, perhaps even tens of different genetic variations. At present, results at the genom-wide level appear to be most promising. The current concept of prediabetes is a realistic foundation for our prediction and prevention of DM2T. A multifactorial, multimarker approach based on our understanding of new pathophysiological factors of DM2T, tries to outline a "map" of prediabetes physiology, and if these tests are combined with sophisticated methods of genetic forecasting of DM2T, this may represent a significant step in our methodology of diabetes prediction. So far however, predictive genetics is limited by the

Diagnostic and therapeutic implications of genetic heterogeneity in myeloid neoplasms uncovered by comprehensive mutational analysis

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Sarah M. Choi

2017-01-01

Full Text Available While growing use of comprehensive mutational analysis has led to the discovery of innumerable genetic alterations associated with various myeloid neoplasms, the under-recognized phenomenon of genetic heterogeneity within such neoplasms creates a potential for diagnostic confusion. Here, we describe two cases where expanded mutational testing led to amendment of an initial diagnosis of chronic myelogenous leukemia with subsequent altered treatment of each patient. We demonstrate the power of comprehensive testing in ensuring appropriate classification of genetically heterogeneous neoplasms, and emphasize thoughtful analysis of molecular and genetic data as an essential component of diagnosis and management.

Alteration of plant meristem function by manipulation of the Retinoblastoma-like plant RRB gene

Science.gov (United States)

Durfee, Tim [Madison, WI; Feiler, Heidi [Albany, CA; Gruissem, Wilhelm [Forch, CH; Jenkins, Susan [Martinez, CA; Roe, Judith [Manhattan, KS; Zambryski, Patricia [Berkeley, CA

2007-01-16

This invention provides methods and compositions for altering the growth, organization, and differentiation of plant tissues. The invention is based on the discovery that, in plants, genetically altering the levels of Retinoblastoma-related gene (RRB) activity produces dramatic effects on the growth, proliferation, organization, and differentiation of plant meristem.

Genetic and chemical knockdown: a complementary strategy for evaluating an anti-infective target

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Ramachandran V

2013-02-01

Full Text Available Vasanthi Ramachandran,1,* Ragini Singh,2,* Xiaoyu Yang,1 Ragadeepthi Tunduguru,1 Subrat Mohapatra,2 Swati Khandelwal,2 Sanjana Patel,2 Santanu Datta21AstraZeneca India R&D, Bangalore, India; 2Cellworks India, Bangalore, India *These authors contributed equally to this workAbstract: The equity of a drug target is principally evaluated by its genetic vulnerability with tools ranging from antisense- and microRNA-driven knockdowns to induced expression of the target protein. In order to upgrade the process of antibacterial target identification and discern its most effective type of inhibition, an in silico toolbox that evaluates its genetic and chemical vulnerability leading either to stasis or cidal outcome was constructed and validated. By precise simulation and careful experimentation using enolpyruvyl shikimate-3-phosphate synthase and its specific inhibitor glyphosate, it was shown that genetic knockdown is distinct from chemical knockdown. It was also observed that depending on the particular mechanism of inhibition, viz competitive, uncompetitive, and noncompetitive, the antimicrobial potency of an inhibitor could be orders of magnitude different. Susceptibility of Escherichia coli to glyphosate and the lack of it in Mycobacterium tuberculosis could be predicted by the in silico platform. Finally, as predicted and simulated in the in silico platform, the translation of growth inhibition to a cidal effect was able to be demonstrated experimentally by altering the carbon source from sorbitol to glucose.Keywords: knockdown, inhibition, in silico, vulnerability

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.

Predicting Flowering Behavior and Exploring Its Genetic Determinism in an Apple Multi-family Population Based on Statistical Indices and Simplified Phenotyping

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Jean-Baptiste Durand

2017-06-01

Full Text Available Irregular flowering over years is commonly observed in fruit trees. The early prediction of tree behavior is highly desirable in breeding programmes. This study aims at performing such predictions, combining simplified phenotyping and statistics methods. Sequences of vegetative vs. floral annual shoots (AS were observed along axes in trees belonging to five apple related full-sib families. Sequences were analyzed using Markovian and linear mixed models including year and site effects. Indices of flowering irregularity, periodicity and synchronicity were estimated, at tree and axis scales. They were used to predict tree behavior and detect QTL with a Bayesian pedigree-based analysis, using an integrated genetic map containing 6,849 SNPs. The combination of a Biennial Bearing Index (BBI with an autoregressive coefficient (γg efficiently predicted and classified the genotype behaviors, despite few misclassifications. Four QTLs common to BBIs and γg and one for synchronicity were highlighted and revealed the complex genetic architecture of the traits. Irregularity resulted from high AS synchronism, whereas regularity resulted from either asynchronous locally alternating or continual regular AS flowering. A relevant and time-saving method, based on a posteriori sampling of axes and statistical indices is proposed, which is efficient to evaluate the tree breeding values for flowering regularity and could be transferred to other species.

Genome-Wide DNA Copy Number Analysis of Acute Lymphoblastic Leukemia Identifies New Genetic Markers Associated with Clinical Outcome.

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Maribel Forero-Castro

Full Text Available Identifying additional genetic alterations associated with poor prognosis in acute lymphoblastic leukemia (ALL is still a challenge.To characterize the presence of additional DNA copy number alterations (CNAs in children and adults with ALL by whole-genome oligonucleotide array (aCGH analysis, and to identify their associations with clinical features and outcome. Array-CGH was carried out in 265 newly diagnosed ALLs (142 children and 123 adults. The NimbleGen CGH 12x135K array (Roche was used to analyze genetic gains and losses. CNAs were analyzed with GISTIC and aCGHweb software. Clinical and biological variables were analyzed. Three of the patients showed chromothripsis (cth6, cth14q and cth15q. CNAs were associated with age, phenotype, genetic subtype and overall survival (OS. In the whole cohort of children, the losses on 14q32.33 (p = 0.019 and 15q13.2 (p = 0.04 were related to shorter OS. In the group of children without good- or poor-risk cytogenetics, the gain on 1p36.11 was a prognostic marker independently associated with shorter OS. In adults, the gains on 19q13.2 (p = 0.001 and Xp21.1 (p = 0.029, and the loss of 17p (p = 0.014 were independent markers of poor prognosis with respect to OS. In summary, CNAs are frequent in ALL and are associated with clinical parameters and survival. Genome-wide DNA copy number analysis allows the identification of genetic markers that predict clinical outcome, suggesting that detection of these genetic lesions will be useful in the management of patients newly diagnosed with ALL.

In vitro short-term exposure to air pollution PM{sub 2.5-0.3} induced cell cycle alterations and genetic instability in a human lung cell coculture model

Energy Technology Data Exchange (ETDEWEB)

Abbas, Imane [Université de Lille, Lille (France); EA4492-UCEIV, Université du Littoral-Côte d’Opale, Dunkerque (France); Lebanese Atomic Energy Commission – CNRS, Beirut (Lebanon); Verdin, Anthony [Université de Lille, Lille (France); EA4492-UCEIV, Université du Littoral-Côte d’Opale, Dunkerque (France); Escande, Fabienne [Centre de Biologie Pathologie, Centre Hospitalier Régional et Universitaire, Lille (France); Saint-Georges, Françoise [Université de Lille, Lille (France); Groupement Hospitalier de l’Institut Catholique de Lille, Lille (France); Cazier, Fabrice [Université de Lille, Lille (France); Centre Commun de Mesures, Université du Littoral-Côte d’Opale, Dunkerque (France); Mulliez, Philippe [Université de Lille, Lille (France); Groupement Hospitalier de l’Institut Catholique de Lille, Lille (France); Courcot, Dominique; Shirali, Pirouz [Université de Lille, Lille (France); EA4492-UCEIV, Université du Littoral-Côte d’Opale, Dunkerque (France); Gosset, Pierre [Université de Lille, Lille (France); Groupement Hospitalier de l’Institut Catholique de Lille, Lille (France); and others

2016-05-15

Although its adverse health effects of air pollution particulate matter (PM2.5) are well-documented and often related to oxidative stress and pro-inflammatory response, recent evidence support the role of the remodeling of the airway epithelium involving the regulation of cell death processes. Hence, the overarching goals of the present study were to use an in vitro coculture model, based on human AM and L132 cells to study the possible alteration of TP53-RB gene signaling pathways (i.e. cell cycle phases, gene expression of TP53, BCL2, BAX, P21, CCND1, and RB, and protein concentrations of their active forms), and genetic instability (i.e. LOH and/or MSI) in the PM{sub 2.5-0.3}-exposed coculture model. PM{sub 2.5-0.3} exposure of human AM from the coculture model induced marked cell cycle alterations after 24 h, as shown by increased numbers of L132 cells in subG1 and S+G2 cell cycle phases, indicating apoptosis and proliferation. Accordingly, activation of the TP53-RB gene signaling pathways after the coculture model exposure to PM{sub 2.5-0.3} was reported in the L132 cells. Exposure of human AM from the coculture model to PM{sub 2.5-0.3} resulted in MS alterations in 3p chromosome multiple critical regions in L132 cell population. Hence, in vitro short-term exposure of the coculture model to PM{sub 2.5-0.3} induced cell cycle alterations relying on the sequential occurrence of molecular abnormalities from TP53-RB gene signaling pathway activation and genetic instability. - Highlights: • Better knowledge on health adverse effects of air pollution PM{sub 2.5}. • Human alveolar macrophage and normal human epithelial lung cell coculture. • Molecular abnormalities from TP53-RB gene signaling pathway. • Loss of heterozygosity and microsatellite instability. • Pathologic changes in morphology and number of cells in relation to airway remodeling.

Modeling human perception of orientation in altered gravity

Science.gov (United States)

Clark, Torin K.; Newman, Michael C.; Oman, Charles M.; Merfeld, Daniel M.; Young, Laurence R.

2015-01-01

Altered gravity environments, such as those experienced by astronauts, impact spatial orientation perception, and can lead to spatial disorientation and sensorimotor impairment. To more fully understand and quantify the impact of altered gravity on orientation perception, several mathematical models have been proposed. The utricular shear, tangent, and the idiotropic vector models aim to predict static perception of tilt in hyper-gravity. Predictions from these prior models are compared to the available data, but are found to systematically err from the perceptions experimentally observed. Alternatively, we propose a modified utricular shear model for static tilt perception in hyper-gravity. Previous dynamic models of vestibular function and orientation perception are limited to 1 G. Specifically, they fail to predict the characteristic overestimation of roll tilt observed in hyper-gravity environments. To address this, we have proposed a modification to a previous observer-type canal-otolith interaction model based upon the hypothesis that the central nervous system (CNS) treats otolith stimulation in the utricular plane differently than stimulation out of the utricular plane. Here we evaluate our modified utricular shear and modified observer models in four altered gravity motion paradigms: (a) static roll tilt in hyper-gravity, (b) static pitch tilt in hyper-gravity, (c) static roll tilt in hypo-gravity, and (d) static pitch tilt in hypo-gravity. The modified models match available data in each of the conditions considered. Our static modified utricular shear model and dynamic modified observer model may be used to help quantitatively predict astronaut perception of orientation in altered gravity environments. PMID:25999822

Modeling Human Perception of Orientation in Altered Gravity

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Torin K. Clark

2015-05-01

Full Text Available Altered gravity environments, such as those experienced by astronauts, impact spatial orientation perception and can lead to spatial disorientation and sensorimotor impairment. To more fully understand and quantify the impact of altered gravity on orientation perception, several mathematical models have been proposed. The utricular shear, tangent, and the idiotropic vector models aim to predict static perception of tilt in hyper-gravity. Predictions from these prior models are compared to the available data, but are found to systematically err from the perceptions experimentally observed. Alternatively, we propose a modified utricular shear model for static tilt perception in hyper-gravity. Previous dynamic models of vestibular function and orientation perception are limited to 1 G. Specifically, they fail to predict the characteristic overestimation of roll tilt observed in hyper-gravity environments. To address this, we have proposed a modification to a previous observer-type canal otolith interaction model based upon the hypothesis that the central nervous system treats otolith stimulation in the utricular plane differently than stimulation out of the utricular plane. Here we evaluate our modified utricular shear and modified observer models in four altered gravity motion paradigms: a static roll tilt in hyper-gravity, b static pitch tilt in hyper-gravity, c static roll tilt in hypo-gravity, and d static pitch tilt in hypo-gravity. The modified models match available data in each of the conditions considered. Our static modified utricular shear model and dynamic modified observer model may be used to help quantitatively predict astronaut perception of orientation in altered gravity environments.

Predicting genome-wide redundancy using machine learning

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Shasha Dennis E

2010-11-01

Full Text Available Abstract Background Gene duplication can lead to genetic redundancy, which masks the function of mutated genes in genetic analyses. Methods to increase sensitivity in identifying genetic redundancy can improve the efficiency of reverse genetics and lend insights into the evolutionary outcomes of gene duplication. Machine learning techniques are well suited to classifying gene family members into redundant and non-redundant gene pairs in model species where sufficient genetic and genomic data is available, such as Arabidopsis thaliana, the test case used here. Results Machine learning techniques that combine multiple attributes led to a dramatic improvement in predicting genetic redundancy over single trait classifiers alone, such as BLAST E-values or expression correlation. In withholding analysis, one of the methods used here, Support Vector Machines, was two-fold more precise than single attribute classifiers, reaching a level where the majority of redundant calls were correctly labeled. Using this higher confidence in identifying redundancy, machine learning predicts that about half of all genes in Arabidopsis showed the signature of predicted redundancy with at least one but typically less than three other family members. Interestingly, a large proportion of predicted redundant gene pairs were relatively old duplications (e.g., Ks > 1, suggesting that redundancy is stable over long evolutionary periods. Conclusions Machine learning predicts that most genes will have a functionally redundant paralog but will exhibit redundancy with relatively few genes within a family. The predictions and gene pair attributes for Arabidopsis provide a new resource for research in genetics and genome evolution. These techniques can now be applied to other organisms.

Stroke genetics: prospects for personalized medicine

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Markus Hugh S

2012-09-01

Full Text Available Abstract Epidemiologic evidence supports a genetic predisposition to stroke. Recent advances, primarily using the genome-wide association study approach, are transforming what we know about the genetics of multifactorial stroke, and are identifying novel stroke genes. The current findings are consistent with different stroke subtypes having different genetic architecture. These discoveries may identify novel pathways involved in stroke pathogenesis, and suggest new treatment approaches. However, the already identified genetic variants explain only a small proportion of overall stroke risk, and therefore are not currently useful in predicting risk for the individual patient. Such risk prediction may become a reality as identification of a greater number of stroke risk variants that explain the majority of genetic risk proceeds, and perhaps when information on rare variants, identified by whole-genome sequencing, is also incorporated into risk algorithms. Pharmacogenomics may offer the potential for earlier implementation of 'personalized genetic' medicine. Genetic variants affecting clopidogrel and warfarin metabolism may identify non-responders and reduce side-effects, but these approaches have not yet been widely adopted in clinical practice.

GENETICS ASPECTS OF DIABETIC NEPHROPATHY

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Oana-Elena Sauca

2010-09-01

Full Text Available Diabetic nephropathy is a clinical syndrome characterized by persistent albuminuria, a relentless decline in GFR, raised arterial blood pressure, and increased relative mortality for cardiovascular diseases. The pathogenesis of diabetic nephropathy is multifactorial, with contributions from metabolic abnormalities, hemodynamic alteration, and various growth and genetic factors. The identification of the main genes would allow the detection of those individuals at high risk for diabetic nephropathy and better understanding of its pathophysiologyas well.The present review discusses the main information available in literature regarding some genetic variants (involved in the renin-angiotensin system, glucose and lipid metabolism and some cytoskeleton proteins that reaffirms the importance of genetic factors in diabetic nephropathy.

[Genetic diagnostics of cancer diseases].

Science.gov (United States)

Cobilanschi, Joana

2013-11-27

Cancer is caused by genetic alterations, but only 10% of the cancer diseases are inherited. The probability for an individual or a family of having inherited cancer, individual consequences of the respective results of genetic testing, as well as its costs and reimbursement by the health insurance must be addressed by expert genetic counseling which at-risk requires special expertise. Identification of a germline mutation which may predispose to a variety of different cancer types allows determination of an individual's specific life time risk in symptomatic as well as in a-symptomatic family members. Identification of the underlying defective gene in heritable cancer disorders also enables optimized preventive and novel therapeutic approaches specifically targeting the underlying molecular pathomechanisms.

Genetic and environmental interactions

International Nuclear Information System (INIS)

Strong, L.C.

1977-01-01

Cancer may result from a multistage process occurring over a long period of time. Presumably, initial and progressive stages of carcinogenesis may be modified by both genetic and environmental factors. Theoretically, genetic factors may alter susceptibility to the carcinogenic effects of an environmental agent at the initial exposure due to variation in metabolism of the carcinogen or variation in specific target cell response to the active carcinogen, or during the latent phase due to numerous factors that might increase the probability of tumor expression, including growth-promoting factors or immunodeficiency states. Observed genetic and environmental interactions in carcinogenesis include an association between genetically determined inducibility of aryl hydrocarbon hydroxylase and smoking-related cancers, familial susceptibility to certain environmental carcinogens, an association between hereditary disorders of mutagenesis and carcinogenesis, and enhancement of tissue-specific, dominantly inherited tumor predisposition by radiation. Multiple primary tumors occur frequently in genetically predisposed individuals. Specific markers for susceptibility must be sought in order that high-risk individuals be identified and appropriate measures taken for early cancer detection or prevention. Study of the nature of the genetically determined susceptibility and interactions with environmental agents may be revealing in the understanding of carcinogenesis in general

Genetics of uveal melanoma and cutaneous melanoma: two of a kind?

NARCIS (Netherlands)

T. van den Bosch (Thomas); E. Kiliç (Emine); A.D.A. Paridaens (Dion); J.E.M.M. de Klein (Annelies)

2010-01-01

textabstractCutaneous melanoma and uveal melanoma both derive from melanocytes but show remarkable differences in tumorigenesis, mode of metastatic spread, genetic alterations, and therapeutic response. In this review we discuss the differences and similarities along with the genetic research

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.

Systems Genetics Reveals the Functional Context of PCOS Loci and Identifies Genetic and Molecular Mechanisms of Disease Heterogeneity

Science.gov (United States)

Xu, Ning; Cui, Jinrui; Mengesha, Emebet; Chen, Yii-Der I.; Taylor, Kent D.; Azziz, Ricardo; Goodarzi, Mark O.

2015-01-01

Genome wide association studies (GWAS) have revealed 11 independent risk loci for polycystic ovary syndrome (PCOS), a common disorder in young women characterized by androgen excess and oligomenorrhea. To put these risk loci and the single nucleotide polymorphisms (SNPs) therein into functional context, we measured DNA methylation and gene expression in subcutaneous adipose tissue biopsies to identify PCOS-specific alterations. Two genes from the LHCGR region, STON1-GTF2A1L and LHCGR, were overexpressed in PCOS. In analysis stratified by obesity, LHCGR was overexpressed only in non-obese PCOS women. Although not differentially expressed in the entire PCOS group, INSR was underexpressed in obese PCOS subjects only. Alterations in gene expression in the LHCGR, RAB5B and INSR regions suggest that SNPs in these loci may be functional and could affect gene expression directly or indirectly via epigenetic alterations. We identified reduced methylation in the LHCGR locus and increased methylation in the INSR locus, changes that are concordant with the altered gene expression profiles. Complex patterns of meQTL and eQTL were identified in these loci, suggesting that local genetic variation plays an important role in gene regulation. We propose that non-obese PCOS women possess significant alterations in LH receptor expression, which drives excess androgen secretion from the ovary. Alternatively, obese women with PCOS possess alterations in insulin receptor expression, with underexpression in metabolic tissues and overexpression in the ovary, resulting in peripheral insulin resistance and excess ovarian androgen production. These studies provide a genetic and molecular basis for the reported clinical heterogeneity of PCOS. PMID:26305227

Systems Genetics Reveals the Functional Context of PCOS Loci and Identifies Genetic and Molecular Mechanisms of Disease Heterogeneity.

Science.gov (United States)

Jones, Michelle R; Brower, Meredith A; Xu, Ning; Cui, Jinrui; Mengesha, Emebet; Chen, Yii-Der I; Taylor, Kent D; Azziz, Ricardo; Goodarzi, Mark O

2015-08-01

Genome wide association studies (GWAS) have revealed 11 independent risk loci for polycystic ovary syndrome (PCOS), a common disorder in young women characterized by androgen excess and oligomenorrhea. To put these risk loci and the single nucleotide polymorphisms (SNPs) therein into functional context, we measured DNA methylation and gene expression in subcutaneous adipose tissue biopsies to identify PCOS-specific alterations. Two genes from the LHCGR region, STON1-GTF2A1L and LHCGR, were overexpressed in PCOS. In analysis stratified by obesity, LHCGR was overexpressed only in non-obese PCOS women. Although not differentially expressed in the entire PCOS group, INSR was underexpressed in obese PCOS subjects only. Alterations in gene expression in the LHCGR, RAB5B and INSR regions suggest that SNPs in these loci may be functional and could affect gene expression directly or indirectly via epigenetic alterations. We identified reduced methylation in the LHCGR locus and increased methylation in the INSR locus, changes that are concordant with the altered gene expression profiles. Complex patterns of meQTL and eQTL were identified in these loci, suggesting that local genetic variation plays an important role in gene regulation. We propose that non-obese PCOS women possess significant alterations in LH receptor expression, which drives excess androgen secretion from the ovary. Alternatively, obese women with PCOS possess alterations in insulin receptor expression, with underexpression in metabolic tissues and overexpression in the ovary, resulting in peripheral insulin resistance and excess ovarian androgen production. These studies provide a genetic and molecular basis for the reported clinical heterogeneity of PCOS.

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.

Genetic Alterations in Gastric Cancer Associated with Helicobacter pylori Infection

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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.

Analysis of genetic effects of nuclear-cytoplasmic interaction on quantitative traits: genetic model for diploid plants.

Science.gov (United States)

Han, Lide; Yang, Jian; Zhu, Jun

2007-06-01

A genetic model was proposed for simultaneously analyzing genetic effects of nuclear, cytoplasm, and nuclear-cytoplasmic interaction (NCI) as well as their genotype by environment (GE) interaction for quantitative traits of diploid plants. In the model, the NCI effects were further partitioned into additive and dominance nuclear-cytoplasmic interaction components. Mixed linear model approaches were used for statistical analysis. On the basis of diallel cross designs, Monte Carlo simulations showed that the genetic model was robust for estimating variance components under several situations without specific effects. Random genetic effects were predicted by an adjusted unbiased prediction (AUP) method. Data on four quantitative traits (boll number, lint percentage, fiber length, and micronaire) in Upland cotton (Gossypium hirsutum L.) were analyzed as a worked example to show the effectiveness of the model.

Sex speeds adaptation by altering the dynamics of molecular evolution.

Science.gov (United States)

McDonald, Michael J; Rice, Daniel P; Desai, Michael M

2016-03-10

Sex and recombination are pervasive throughout nature despite their substantial costs. Understanding the evolutionary forces that maintain these phenomena is a central challenge in biology. One longstanding hypothesis argues that sex is beneficial because recombination speeds adaptation. Theory has proposed several distinct population genetic mechanisms that could underlie this advantage. For example, sex can promote the fixation of beneficial mutations either by alleviating interference competition (the Fisher-Muller effect) or by separating them from deleterious load (the ruby in the rubbish effect). Previous experiments confirm that sex can increase the rate of adaptation, but these studies did not observe the evolutionary dynamics that drive this effect at the genomic level. Here we present the first, to our knowledge, comparison between the sequence-level dynamics of adaptation in experimental sexual and asexual Saccharomyces cerevisiae populations, which allows us to identify the specific mechanisms by which sex speeds adaptation. We find that sex alters the molecular signatures of evolution by changing the spectrum of mutations that fix, and confirm theoretical predictions that it does so by alleviating clonal interference. We also show that substantially deleterious mutations hitchhike to fixation in adapting asexual populations. In contrast, recombination prevents such mutations from fixing. Our results demonstrate that sex both speeds adaptation and alters its molecular signature by allowing natural selection to more efficiently sort beneficial from deleterious mutations.

How Darwinian reductionism refutes genetic determinism.

Science.gov (United States)

Rosoff, Philip M; Rosenberg, Alex

2006-03-01

Genetic determinism labels the morally problematical claim that some socially significant traits, traits we care about, such as sexual orientation, gender roles, violence, alcoholism, mental illness, intelligence, are largely the results of the operation of genes and not much alterable by environment, learning or other human intervention. Genetic determinism does not require that genes literally fix these socially significant traits, but rather that they constrain them within narrow channels beyond human intervention. In this essay we analyze genetic determinism in light of what is now known about the inborn error of metabolism phenylketonuria (PKU), which has for so long been the poster child 'simple' argument in favor of some form of genetic determinism. We demonstrate that this case proves the exact opposite of what it has been proposed to support and provides a strong refutation of genetic determinism in all its guises.

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

Innate Immune Signalling Genetics of Pain, Cognitive Dysfunction and Sickness Symptoms in Cancer Pain Patients Treated with Transdermal Fentanyl.

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Daniel T Barratt

Full Text Available Common adverse symptoms of cancer and chemotherapy are a major health burden; chief among these is pain, with opioids including transdermal fentanyl the mainstay of treatment. Innate immune activation has been implicated generally in pain, opioid analgesia, cognitive dysfunction, and sickness type symptoms reported by cancer patients. We aimed to determine if genetic polymorphisms in neuroimmune activation pathways alter the serum fentanyl concentration-response relationships for pain control, cognitive dysfunction, and other adverse symptoms, in cancer pain patients. Cancer pain patients (468 receiving transdermal fentanyl were genotyped for 31 single nucleotide polymorphisms in 19 genes: CASP1, BDNF, CRP, LY96, IL6, IL1B, TGFB1, TNF, IL10, IL2, TLR2, TLR4, MYD88, IL6R, OPRM1, ARRB2, COMT, STAT6 and ABCB1. Lasso and backward stepwise generalised linear regression were used to identify non-genetic and genetic predictors, respectively, of pain control (average Brief Pain Inventory < 4, cognitive dysfunction (Mini-Mental State Examination ≤ 23, sickness response and opioid adverse event complaint. Serum fentanyl concentrations did not predict between-patient variability in these outcomes, nor did genetic factors predict pain control, sickness response or opioid adverse event complaint. Carriers of the MYD88 rs6853 variant were half as likely to have cognitive dysfunction (11/111 than wild-type patients (69/325, with a relative risk of 0.45 (95% CI: 0.27 to 0.76 when accounting for major non-genetic predictors (age, Karnofsky functional score. This supports the involvement of innate immune signalling in cognitive dysfunction, and identifies MyD88 signalling pathways as a potential focus for predicting and reducing the burden of cognitive dysfunction in cancer pain patients.

The Role of BRCA2 Mutation Status as Diagnostic, Predictive, and Prognosis Biomarker for Pancreatic Cancer

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Javier Martinez-Useros

2016-01-01

Full Text Available Pancreatic cancer is one of the deadliest cancers worldwide, and life expectancy after diagnosis is often short. Most pancreatic tumours appear sporadically and have been highly related to habits such as cigarette smoking, high alcohol intake, high carbohydrate, and sugar consumption. Other observational studies have suggested the association between pancreatic cancer and exposure to arsenic, lead, or cadmium. Aside from these factors, chronic pancreatitis and diabetes have also come to be considered as risk factors for these kinds of tumours. Studies have found that 10% of pancreatic cancer cases arise from an inherited syndrome related to some genetic alterations. One of these alterations includes mutation in BRCA2 gene. BRCA2 mutations impair DNA damage response and homologous recombination by direct regulation of RAD51. In light of these findings that link genetic factors to tumour development, DNA damage agents have been proposed as target therapies for pancreatic cancer patients carrying BRCA2 mutations. Some of these drugs include platinum-based agents and PARP inhibitors. However, the acquired resistance to PARP inhibitors has created a need for new chemotherapeutic strategies to target BRCA2. The present systematic review collects and analyses the role of BRCA2 alterations to be used in early diagnosis of an inherited syndrome associated with familiar cancer and as a prognostic and predictive biomarker for the management of pancreatic cancer patients.

Prognostic impact of array-based genomic profiles in esophageal squamous cell cancer

DEFF Research Database (Denmark)

Carneiro, Ana; Isinger, Anna; Karlsson, Anna

2008-01-01

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is a genetically complex tumor type and a major cause of cancer related mortality. Although distinct genetic alterations have been linked to ESCC development and prognosis, the genetic alterations have not gained clinical applicability. We...... interdependent alterations and deranged pathways were identified and copy number changes were correlated to stage, differentiation and survival. RESULTS: Copy number alterations affected median 19% of the genome and included recurrent gains of chromosome regions 5p, 7p, 7q, 8q, 10q, 11q, 12p, 14q, 16p, 17p, 19p......p13.3 independently predicted poor survival in multivariate analysis. CONCLUSION: aCGH profiling verified genetic complexity in ESCC and herein identified imbalances of multiple central tumorigenic pathways. Distinct gains correlate with clinicopathological variables and independently predict...

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

Acquisition of Genetic Aberrations by Activation-Induced Cytidine Deaminase (AID) during Inflammation-Associated Carcinogenesis

International Nuclear Information System (INIS)

Takai, Atsushi; Marusawa, Hiroyuki; Chiba, Tsutomu

2011-01-01

Genetic abnormalities such as nucleotide alterations and chromosomal disorders that accumulate in various tumor-related genes have an important role in cancer development. The precise mechanism of the acquisition of genetic aberrations, however, remains unclear. Activation-induced cytidine deaminase (AID), a nucleotide editing enzyme, is essential for the diversification of antibody production. AID is expressed only in activated B lymphocytes under physiologic conditions and induces somatic hypermutation and class switch recombination in immunoglobulin genes. Inflammation leads to aberrant AID expression in various gastrointestinal organs and increased AID expression contributes to cancer development by inducing genetic alterations in epithelial cells. Studies of how AID induces genetic disorders are expected to elucidate the mechanism of inflammation-associated carcinogenesis

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

Population genetics of non-genetic traits: Evolutionary roles of stochasticity in gene expression

KAUST Repository

Mineta, Katsuhiko

2015-05-01

The role of stochasticity in evolutionary genetics has long been debated. To date, however, the potential roles of non-genetic traits in evolutionary processes have been largely neglected. In molecular biology, growing evidence suggests that stochasticity in gene expression (SGE) is common and that SGE has major impacts on phenotypes and fitness. Here, we provide a general overview of the potential effects of SGE on population genetic parameters, arguing that SGE can indeed have a profound effect on evolutionary processes. Our analyses suggest that SGE potentially alters the fate of mutations by influencing effective population size and fixation probability. In addition, a genetic control of SGE magnitude could evolve under certain conditions, if the fitness of the less-fit individual increases due to SGE and environmental fluctuation. Although empirical evidence for our arguments is yet to come, methodological developments for precisely measuring SGE in living organisms will further advance our understanding of SGE-driven evolution.

Population genetics of non-genetic traits: Evolutionary roles of stochasticity in gene expression

KAUST Repository

Mineta, Katsuhiko; Matsumoto, Tomotaka; Osada, Naoki; Araki, Hitoshi

2015-01-01

The role of stochasticity in evolutionary genetics has long been debated. To date, however, the potential roles of non-genetic traits in evolutionary processes have been largely neglected. In molecular biology, growing evidence suggests that stochasticity in gene expression (SGE) is common and that SGE has major impacts on phenotypes and fitness. Here, we provide a general overview of the potential effects of SGE on population genetic parameters, arguing that SGE can indeed have a profound effect on evolutionary processes. Our analyses suggest that SGE potentially alters the fate of mutations by influencing effective population size and fixation probability. In addition, a genetic control of SGE magnitude could evolve under certain conditions, if the fitness of the less-fit individual increases due to SGE and environmental fluctuation. Although empirical evidence for our arguments is yet to come, methodological developments for precisely measuring SGE in living organisms will further advance our understanding of SGE-driven evolution.

Predictable Phenotypes of Antibiotic Resistance Mutations.

Science.gov (United States)

Knopp, M; Andersson, D I

2018-05-15

Antibiotic-resistant bacteria represent a major threat to our ability to treat bacterial infections. Two factors that determine the evolutionary success of antibiotic resistance mutations are their impact on resistance level and the fitness cost. Recent studies suggest that resistance mutations commonly show epistatic interactions, which would complicate predictions of their stability in bacterial populations. We analyzed 13 different chromosomal resistance mutations and 10 host strains of Salmonella enterica and Escherichia coli to address two main questions. (i) Are there epistatic interactions between different chromosomal resistance mutations? (ii) How does the strain background and genetic distance influence the effect of chromosomal resistance mutations on resistance and fitness? Our results show that the effects of combined resistance mutations on resistance and fitness are largely predictable and that epistasis remains rare even when up to four mutations were combined. Furthermore, a majority of the mutations, especially target alteration mutations, demonstrate strain-independent phenotypes across different species. This study extends our understanding of epistasis among resistance mutations and shows that interactions between different resistance mutations are often predictable from the characteristics of the individual mutations. IMPORTANCE The spread of antibiotic-resistant bacteria imposes an urgent threat to public health. The ability to forecast the evolutionary success of resistant mutants would help to combat dissemination of antibiotic resistance. Previous studies have shown that the phenotypic effects (fitness and resistance level) of resistance mutations can vary substantially depending on the genetic context in which they occur. We conducted a broad screen using many different resistance mutations and host strains to identify potential epistatic interactions between various types of resistance mutations and to determine the effect of strain

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

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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.

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)

Periodontal disease associated to systemic genetic disorders.

Science.gov (United States)

Nualart Grollmus, Zacy Carola; Morales Chávez, Mariana Carolina; Silvestre Donat, Francisco Javier

2007-05-01

A number of systemic disorders increase patient susceptibility to periodontal disease, which moreover evolves more rapidly and more aggressively. The underlying factors are mainly related to alterations in immune, endocrine and connective tissue status. These alterations are associated with different pathologies and syndromes that generate periodontal disease either as a primary manifestation or by aggravating a pre-existing condition attributable to local factors. This is where the role of bacterial plaque is subject to debate. In the presence of qualitative or quantitative cellular immune alterations, periodontal disease may manifest early on a severe localized or generalized basis--in some cases related to the presence of plaque and/or specific bacteria (severe congenital neutropenia or infantile genetic agranulocytosis, Chediak-Higiashi syndrome, Down syndrome and Papillon-Lefévre syndrome). In the presence of humoral immune alterations, periodontal damage may result indirectly as a consequence of alterations in other systems. In connective tissue disorders, bacterial plaque and alterations of the periodontal tissues increase patient susceptibility to gingival inflammation and alveolar resorption (Marfan syndrome and Ehler-Danlos syndrome). The management of periodontal disease focuses on the control of infection and bacterial plaque by means of mechanical and chemical methods. Periodontal surgery and even extraction of the most seriously affected teeth have also been suggested. There are variable degrees of consensus regarding the background systemic disorder, as in the case of Chediak-Higiashi syndrome, where antibiotic treatment proves ineffective; in severe congenital neutropenia or infantile genetic agranulocytosis, where antibiotic prophylaxis is suggested; and in Papillon-Lefévre syndrome, where an established treatment protocol is available.

Predictive medicine

NARCIS (Netherlands)

Boenink, Marianne; ten Have, Henk

2015-01-01

In the last part of the twentieth century, predictive medicine has gained currency as an important ideal in biomedical research and health care. Research in the genetic and molecular basis of disease suggested that the insights gained might be used to develop tests that predict the future health

Genetic architecture of complex traits and accuracy of genomic prediction: coat colour, milk-fat percentage, and type in Holstein cattle as contrasting model traits.

Directory of Open Access Journals (Sweden)

Ben J Hayes

2010-09-01

Full Text Available Prediction of genetic merit using dense SNP genotypes can be used for estimation of breeding values for selection of livestock, crops, and forage species; for prediction of disease risk; and for forensics. The accuracy of these genomic predictions depends in part on the genetic architecture of the trait, in particular number of loci affecting the trait and distribution of their effects. Here we investigate the difference among three traits in distribution of effects and the consequences for the accuracy of genomic predictions. Proportion of black coat colour in Holstein cattle was used as one model complex trait. Three loci, KIT, MITF, and a locus on chromosome 8, together explain 24% of the variation of proportion of black. However, a surprisingly large number of loci of small effect are necessary to capture the remaining variation. A second trait, fat concentration in milk, had one locus of large effect and a host of loci with very small effects. Both these distributions of effects were in contrast to that for a third trait, an index of scores for a number of aspects of cow confirmation ("overall type", which had only loci of small effect. The differences in distribution of effects among the three traits were quantified by estimating the distribution of variance explained by chromosome segments containing 50 SNPs. This approach was taken to account for the imperfect linkage disequilibrium between the SNPs and the QTL affecting the traits. We also show that the accuracy of predicting genetic values is higher for traits with a proportion of large effects (proportion black and fat percentage than for a trait with no loci of large effect (overall type, provided the method of analysis takes advantage of the distribution of loci effects.

Dynamic modeling of genetic networks using genetic algorithm and S-system.

Science.gov (United States)

Kikuchi, Shinichi; Tominaga, Daisuke; Arita, Masanori; Takahashi, Katsutoshi; Tomita, Masaru

2003-03-22

The modeling of system dynamics of genetic networks, metabolic networks or signal transduction cascades from time-course data is formulated as a reverse-problem. Previous studies focused on the estimation of only network structures, and they were ineffective in inferring a network structure with feedback loops. We previously proposed a method to predict not only the network structure but also its dynamics using a Genetic Algorithm (GA) and an S-system formalism. However, it could predict only a small number of parameters and could rarely obtain essential structures. In this work, we propose a unified extension of the basic method. Notable improvements are as follows: (1) an additional term in its evaluation function that aims at eliminating futile parameters; (2) a crossover method called Simplex Crossover (SPX) to improve its optimization ability; and (3) a gradual optimization strategy to increase the number of predictable parameters. The proposed method is implemented as a C program called PEACE1 (Predictor by Evolutionary Algorithms and Canonical Equations 1). Its performance was compared with the basic method. The comparison showed that: (1) the convergence rate increased about 5-fold; (2) the optimization speed was raised about 1.5-fold; and (3) the number of predictable parameters was increased about 5-fold. Moreover, we successfully inferred the dynamics of a small genetic network constructed with 60 parameters for 5 network variables and feedback loops using only time-course data of gene expression.

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, ...

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.

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.

Molecular-genetic analysis of two cases with retinoblastoma ...

Indian Academy of Sciences (India)

Unknown

Effective counselling and management of retinoblastoma families using genetic information is presently practised in many parts of ... to chromosomal deletion, single-nucleotide alteration, microdeletion, loss ... informed consent of the parent.

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.

Computational Analysis of Single Nucleotide Polymorphisms Associated with Altered Drug Responsiveness in Type 2 Diabetes

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Valerio Costa

2016-06-01

Full Text Available Type 2 diabetes (T2D is one of the most frequent mortality causes in western countries, with rapidly increasing prevalence. Anti-diabetic drugs are the first therapeutic approach, although many patients develop drug resistance. Most drug responsiveness variability can be explained by genetic causes. Inter-individual variability is principally due to single nucleotide polymorphisms, and differential drug responsiveness has been correlated to alteration in genes involved in drug metabolism (CYP2C9 or insulin signaling (IRS1, ABCC8, KCNJ11 and PPARG. However, most genome-wide association studies did not provide clues about the contribution of DNA variations to impaired drug responsiveness. Thus, characterizing T2D drug responsiveness variants is needed to guide clinicians toward tailored therapeutic approaches. Here, we extensively investigated polymorphisms associated with altered drug response in T2D, predicting their effects in silico. Combining different computational approaches, we focused on the expression pattern of genes correlated to drug resistance and inferred evolutionary conservation of polymorphic residues, computationally predicting the biochemical properties of polymorphic proteins. Using RNA-Sequencing followed by targeted validation, we identified and experimentally confirmed that two nucleotide variations in the CAPN10 gene—currently annotated as intronic—fall within two new transcripts in this locus. Additionally, we found that a Single Nucleotide Polymorphism (SNP, currently reported as intergenic, maps to the intron of a new transcript, harboring CAPN10 and GPR35 genes, which undergoes non-sense mediated decay. Finally, we analyzed variants that fall into non-coding regulatory regions of yet underestimated functional significance, predicting that some of them can potentially affect gene expression and/or post-transcriptional regulation of mRNAs affecting the splicing.

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.

Review: Biological imprinting: Some genetic considerations | Saad ...

African Journals Online (AJOL)

... as for interpretation of possible mechanisms implicated in its occurrence. Keywords: Genetic imprinting; Mutations; Re-sense mutation; Epigenetic alterations; DNA methylation/demethylation; Parthenogenesis; Position-effect variegation; Post-fertilization genomic imprinting; microRNA; Chromatin modifications; Pyknons ...

Genetic and molecular analysis of radon-induced rat lung tumours

International Nuclear Information System (INIS)

Guilly, M.N.; Joubert, Ch.; Levalois, C.; Dano, L.; Chevillard, S.

2002-01-01

We have a model of radon-induced rat lung tumours, which allow us to analyse the cytogenetic and molecular alterations of the tumours. The aim is to better understand the mechanisms of radio-induced carcinogenesis and to define if it exists a specificity of radio-induced genetic alterations as compared to the genetic alterations found in the sporadic tumours. We have started our analysis by developing global cytogenetic and molecular approaches. We have shown that some alterations are recurrent. The genes that are potentially involved are the oncogene MET and the tumour suppressor Bene p16, which are also frequently altered in human lung tumours. Simultaneously, we have focussed our analysis by targeting the search of mutation in the tumour suppressor gene TP3. We have found that 8 of 39 tumours were mutated by deletion in the coding sequence of TP53. This high frequency of deletion, which is not observed in the human p53 mutation database could constitute a signature of radio-induced alterations. On this assumption, this type of alteration should not be only found on TP53 Bene but also in other suppressor genes which are inactivated by a mutation such as p16 for example. The work we are carrying out on radio-induced tumours among humans and animals is directed to this end. (author)

Habitat Predicts Levels of Genetic Admixture in Saccharomyces cerevisiae

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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.

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.

Systems Genetics Reveals the Functional Context of PCOS Loci and Identifies Genetic and Molecular Mechanisms of Disease Heterogeneity.

Directory of Open Access Journals (Sweden)

Michelle R Jones

2015-08-01

Full Text Available Genome wide association studies (GWAS have revealed 11 independent risk loci for polycystic ovary syndrome (PCOS, a common disorder in young women characterized by androgen excess and oligomenorrhea. To put these risk loci and the single nucleotide polymorphisms (SNPs therein into functional context, we measured DNA methylation and gene expression in subcutaneous adipose tissue biopsies to identify PCOS-specific alterations. Two genes from the LHCGR region, STON1-GTF2A1L and LHCGR, were overexpressed in PCOS. In analysis stratified by obesity, LHCGR was overexpressed only in non-obese PCOS women. Although not differentially expressed in the entire PCOS group, INSR was underexpressed in obese PCOS subjects only. Alterations in gene expression in the LHCGR, RAB5B and INSR regions suggest that SNPs in these loci may be functional and could affect gene expression directly or indirectly via epigenetic alterations. We identified reduced methylation in the LHCGR locus and increased methylation in the INSR locus, changes that are concordant with the altered gene expression profiles. Complex patterns of meQTL and eQTL were identified in these loci, suggesting that local genetic variation plays an important role in gene regulation. We propose that non-obese PCOS women possess significant alterations in LH receptor expression, which drives excess androgen secretion from the ovary. Alternatively, obese women with PCOS possess alterations in insulin receptor expression, with underexpression in metabolic tissues and overexpression in the ovary, resulting in peripheral insulin resistance and excess ovarian androgen production. These studies provide a genetic and molecular basis for the reported clinical heterogeneity of PCOS.

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.

Modelling glass alteration in an altered argillaceous environment

International Nuclear Information System (INIS)

Bildstein, O.; Trotignon, L.; Pozo, C.; Jullien, M.

2007-01-01

The long term behaviour of materials such as glass, steel and clay has been investigated in the context of deep geological disposal of radioactive wastes. The interactions between vitrified wastes, canister corrosion products (CPs) and clay are studied using a modified version of the reaction-transport code Crunch, especially looking at pH changes and possible cementation at the interface with the clayey materials. These perturbations may indeed affect the lifetime of glass matrix in deep repositories, e.g., high pH enhances the rate of glass alteration. This work focuses on the argillite of Bure. The calculations were performed at 323 K with a glass alteration rate switching from a high initial rate to a residual rate according to the sorption capacity of CPs. The time at which this sorption capacity is saturated is crucial to the system in terms of wastes package lifetime. The results show that the glass alteration imposes a high pH value at the interface with CPs and clay: up to a value of 9.2, compared to 7.3 which is the initial pH value in the argillite. Experimental data show that the rate of glass alteration is much higher in such pH conditions. For a R7T7-type glass, the rate is about five times higher at pH 9 than at pH 7. This pH perturbation migrates through the clayey domain as a result of the migration of mobile elements such as boron and sodium, and despite the existence of strong pH buffers in the argillite. The cementation of porosity at the interface between glass and clay is predicted by the model due to the massive precipitation of iron corrosion products and glass alteration products. At this point of the evolution of the system, the pH starts to decrease and the alteration rate of the glass could be significantly reduced. This porosity clogging effect is difficult to confirm by experiments especially since existing data on short term experiments tend to show a pervasive precipitation of silica in the domain instead of a localized precipitation

Validation of variants in SLC28A3 and UGT1A6 as genetic markers predictive of anthracycline-induced cardiotoxicity in children

NARCIS (Netherlands)

Visscher, H.; Ross, C. J. D.; Rassekh, S. R.; Sandor, G. S. S.; Caron, H. N.; van Dalen, E. C.; Kremer, L. C.; van der Pal, H. J.; Rogers, P. C.; Rieder, M. J.; Carleton, B. C.; Hayden, M. R.; Hayden, Michael; Carleton, Bruce; Ross, Colin; MacLeod, Stuart; Wasserman, Wyeth; Mitton, Craig; Smith, Anne; Hildebrand, Claudette; Pastrana, Lucila Castro; Ghannadan, Reza; Rassekh, Rod; Lim, Jonathan; Carter, Catherine; Miao, Fudan; Visscher, Henk; Pussegoda, Kusala; Higginson, Michelle; Butland, Stefanie; Yazdanpanah, Mojgan; Nijssen-Jordan, Cheri; Johnson, David; Verbeek, Linda; Kaczowka, Rick; Stevenson, Patti; Grundy, Paul; Stobart, Kent; Wilson, Bev; Desai, Sunil; Spavor, Maria; Churcher, Linda; Chow, Terence; Hall, Kevin; Honcharik, Nick; Israels, Sara; Chan, Shanna; Garnham, Byron; Staub, Michelle; Rieder, Michael; Malkin, Becky; Portwine, Carol; Cranston, Amy; Koren, Gideon; Ito, Shinya; Nathan, Paul; Greenberg, Mark; Bournissen, Facundo Garcia; Inoue, Miho; Sakaguchi, Sachi; Tanaka, Toshihiro; Fujii, Hisaki; Ogawa, Mina; Ingram, Ryoko; Kamiya, Taro; Karande, Smita; Silva, Mariana; Willing, Stephanie; Vaillancourt, Régis; Elliott-Miller, Pat; Johnston, Donna; Mankoo, Herpreet; Wong, Elaine; Wilson, Brenda; O'Connor, Lauren; Maher, Maurica; Bussières, Jean-Francois; Lebel, Denis; Barret, Pierre; Closon, Aurélie; Dubé, Marie-Pierre; Phillips, Michael; Jabado, Nada; Santo, Anelise Espirito; Nagy, Martine; Avard, Denise; Murray, Margaret; Boliver, Darlene; Tiller, Marilyn

2013-01-01

The use of anthracyclines as effective antineoplastic drugs is limited by the occurrence of cardiotoxicity. Multiple genetic variants predictive of anthracycline-induced cardiotoxicity (ACT) in children were recently identified. The current study was aimed to assess replication of these findings in

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...

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.

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.