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Relevant bibliographies by topics / Gene-For-Gene interaction

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Academic literature on the topic 'Gene-For-Gene interaction'

Author: Grafiati

Published: 8 June 2024

Last updated: 31 July 2025

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Journal articles on the topic "Gene-For-Gene interaction"

1

Wang, Yaping, Donghui Li, and Peng Wei. "Powerful Tukey's One Degree-of-Freedom Test for Detecting Gene-Gene and Gene-Environment Interactions." Cancer Informatics 14s2 (January 2015): CIN.S17305. http://dx.doi.org/10.4137/cin.s17305.

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Genome-wide association studies (GWASs) have identified thousands of single nucleotide polymorphisms (SNPs) robustly associated with hundreds of complex human diseases including cancers. However, the large number of G WAS-identified genetic loci only explains a small proportion of the disease heritability. This “missing heritability” problem has been partly attributed to the yet-to-be-identified gene-gene (G × G) and gene-environment (G × E) interactions. In spite of the important roles of G × G and G × E interactions in understanding disease mechanisms and filling in the missing heritability,

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Zhang, Jigang, Jian Li, and Hong-Wen Deng. "Identifying Gene Interaction Enrichment for Gene Expression Data." PLoS ONE 4, no. 11 (2009): e8064. http://dx.doi.org/10.1371/journal.pone.0008064.

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Mechanic, Leah E., Brian T. Luke, Julie E. Goodman, Stephen J. Chanock, and Curtis C. Harris. "Polymorphism Interaction Analysis (PIA): a method for investigating complex gene-gene interactions." BMC Bioinformatics 9, no. 1 (2008): 146. http://dx.doi.org/10.1186/1471-2105-9-146.

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Zhou, R., M. Wang, W. Li, et al. "Gene-Gene Interactions among SPRYs for Nonsyndromic Cleft Lip/Palate." Journal of Dental Research 98, no. 2 (2018): 180–85. http://dx.doi.org/10.1177/0022034518801537.

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Nonsyndromic cleft lip with or without cleft palate (NSCL/P) is a common birth defect with a complex genetic architecture. Gene-gene interactions have been increasingly regarded as contributing to the etiology of NSCL/P. A recent genome-wide association study revealed that a novel single-nucleotide polymorphism at SPRY1 in 4q28.1 showed a significant association with NSCL/P. In the current study, we explored the role of 3 SPRY genes in the etiology of NSCL/P by detecting gene-gene interactions: SPRY1, SPRY2, and SPRY4—with SPRY3 excluded due to its special location on the X chromosome. We sele

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Zhou, Xiangdong, Keith C. C. Chan, Zhihua Huang, and Jingbin Wang. "Determining dependency and redundancy for identifying gene–gene interaction associated with complex disease." Journal of Bioinformatics and Computational Biology 18, no. 05 (2020): 2050035. http://dx.doi.org/10.1142/s0219720020500353.

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As interactions among genetic variants in different genes can be an important factor for predicting complex diseases, many computational methods have been proposed to detect if a particular set of genes has interaction with a particular complex disease. However, even though many such methods have been shown to be useful, they can be made more effective if the properties of gene–gene interactions can be better understood. Towards this goal, we have attempted to uncover patterns in gene–gene interactions and the patterns reveal an interesting property that can be reflected in an inequality that

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Sa, Jian, Xu Liu, Tao He, Guifen Liu, and Yuehua Cui. "A Nonlinear Model for Gene-Based Gene-Environment Interaction." International Journal of Molecular Sciences 17, no. 6 (2016): 882. http://dx.doi.org/10.3390/ijms17060882.

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Chen, Zhongxue. "Testing for gene-gene interaction in case-control GWAS." Statistics and Its Interface 10, no. 2 (2017): 267–77. http://dx.doi.org/10.4310/sii.2017.v10.n2.a10.

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Corvol, Harriet, Anthony De Giacomo, Celeste Eng, et al. "Genetic ancestry modifies pharmacogenetic gene–gene interaction for asthma." Pharmacogenetics and Genomics 19, no. 7 (2009): 489–96. http://dx.doi.org/10.1097/fpc.0b013e32832c440e.

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Song, Minsun, and Dan L. Nicolae. "Restricted parameter space models for testing gene-gene interaction." Genetic Epidemiology 33, no. 5 (2009): 386–93. http://dx.doi.org/10.1002/gepi.20392.

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Li, Qing, Yoonhee Kim, Bhoom Suktitipat, et al. "Gene-Gene Interaction AmongWNTGenes for Oral Cleft in Trios." Genetic Epidemiology 39, no. 5 (2015): 385–94. http://dx.doi.org/10.1002/gepi.21888.

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Dissertations / Theses on the topic "Gene-For-Gene interaction"

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Assareh, Amin. "OPTIMIZING DECISION TREE ENSEMBLES FOR GENE-GENE INTERACTION DETECTION." Kent State University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=kent1353971575.

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Bendahmane, Abdelhafid. "Analysis of a gene-for-gene interaction associated with Rx-mediated resistance to potato virus X." Thesis, University of East Anglia, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.389350.

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Aleknonytė-Resch, Milda [Verfasser], Astrid [Akademischer Betreuer] Dempfle, and Hinrich [Gutachter] Schulenburg. "The Validity and Statistical Power of the Case-Only Study Design for Interaction Analysis : Gene-Gene Interaction and the Role of Genotype Imputation in Gene-Environment Interaction / Milda Aleknonytė-Resch ; Gutachter: Hinrich Schulenburg ; Betreuer: Astrid Dempfle." Kiel : Universitätsbibliothek Kiel, 2021. http://d-nb.info/1229916962/34.

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Elisson, Hanna. "Uncertainty in Genetic Mapping and Gene Interaction for Diabetes in Rats." Thesis, Uppsala University, Department of Mathematics, 2000. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-122559.

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MacGowan, Alice Laura. "Embryonic retinoid deficiency and congenital malformation : evidence for gene-environment interaction." Thesis, University of Sheffield, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.398657.

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Thi, Cam Thach Doan. "A GRAPHICAL USER INTERFACE FOR LARGE-SCALE GENE EXPRESSION ANALYSIS." Thesis, Högskolan i Borås, Institutionen Handels- och IT-högskolan, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-20870.

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Recently, the whole-genome expression analysis – which is analyzing most or all of the genes in biological systems, and is a rich and powerful way to discover gene pathway - has become increasingly affordable because of the increasing amount of microarray data available in public databases. Additionally, due to the enormously available information content in these repositories, researchers have to spend large amount of time to decide on the right information to proceed. There should be an application to assist biological researchers reducing the time in finding good data sets to analyze. In th

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Korkmaz, Gulberal Kircicegi Yoksul. "Mining Microarray Data For Biologically Important Gene Sets." Phd thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12614266/index.pdf.

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Microarray technology enables researchers to measure the expression levels of thousands of genes simultaneously to understand relationships between genes, extract pathways, and in general understand a diverse amount of biological processes such as diseases and cell cycles. While microarrays provide the great opportunity of revealing information about biological processes, it is a challenging task to mine the huge amount of information contained in the microarray datasets. Generally, since an accurate model for the data is missing, first a clustering algorithm is applied and then the resulting

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Piqueras, Matias. "HERITABILITY FOR SOCIAL TRUST ACROSS SOCIOECONOMIC STATUS: : Is There a Gene-Environment Interaction?" Thesis, Uppsala universitet, Statsvetenskapliga institutionen, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-394876.

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In political science literature, the development of social trust is often explained in terms of the influence of different environmental factors, socioeconomic status (SES) being one of the most important. Yet, even though there is empirical support of a genetic component in the expression of social trust, less is known about its interaction with environmental factors. The present study aims to explore heritability of social trust across socioeconomic status using a twin-design that tests potential gene-environment (GxE) interactions. Moreover, the study explicitly tests the hypothesis that di

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Cai, Yu. "Molecular Characterization of the mop2, a Gene Required for Epigenetic Silencing." Diss., The University of Arizona, 2006. http://hdl.handle.net/10150/195361.

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The mop2 gene is required for epigenetic silencing; it was originally defined as a mutation, Mop2-1, which when dominant prevented paramutation at b1. Paramutation is an allele communication that causes a mitotically and meiotically heritable change in gene expression. Mop2-1 was subsequently shown to be involved in maintaining the silenced paramutant state and to prevent dsRNA-mediated transcriptional gene silencing (activities revealed only when the mutation is homozygous). Understanding the product encoded by mop2 will help dissect the underlying mechanisms involved in paramutation and

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Mietzsch, Mario [Verfasser]. "Adeno-Associated Virus Vectors for Gene Therapy : From Scalable Production Systems via Serotype-Specific Glycan Interaction Patterns to Gene Transfer Applications / Mario Mietzsch." Berlin : Freie Universität Berlin, 2014. http://d-nb.info/1055942203/34.

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Books on the topic "Gene-For-Gene interaction"

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R, Crute I., Holub E. B, Burdon J. J, and British Society for Plant Pathology., eds. The gene-for-gene relationship in plant-parasite interactions. CAB International, 1997.

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Håkansssson, Gunilla. Nuclear-mitochondrial interactions and its relevance for male sterility in Nicotiana: Analysis of mitochondrial genome organization, gene expression and respiration in male-fertile and alloplasmic male-sterile materials. Swedish University of Agricultural Sciences, Dept. of Plant Breeding, 1992.

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Sasaki, Joni Y., Jessica LeClair, Alexandria West, and Heejung S. Kim. The Gene–Culture Interaction Framework and Implications for Health. Edited by Joan Y. Chiao, Shu-Chen Li, Rebecca Seligman, and Robert Turner. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199357376.013.20.

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Razzoli, Maria, Alessandro Bartolomucci, and Valeria Carola. Gene-by-Environment Mouse Models for Mood Disorders. Edited by Turhan Canli. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199753888.013.013.

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Much of the impact of genes on mood disorders likely depends on interactions between genes and the environment. Recent studies demonstrating an interaction between specific genes and life stressful events (early and/or adult) in the modulation of several mood disorders (e.g., serotonin transporter and brain-derived neurotrophic factor genes) have compelled researchers to incorporate information about adverse environmental experiences into the study of genetic risk factors; these same gene-by-environment (G×E) interactions have been identified in mouse models. Notably, G×E not yet described in

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He, Zihuai, Michael Windle, James Y. Dai, and Caroline Y. Doyle. Statistical Approaches to Gene X Environment Interactions for Complex Phenotypes. MIT Press, 2016.

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Statistical Approaches to Gene X Environment Interactions for Complex Phenotypes. MIT Press, 2016.

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Klengel, Torsten, Lauren A. M. Lebois, Sheila Gaynor, and Guia Guffanti. Genetics and Gene–Environment Interaction. Edited by Frederick J. Stoddard, David M. Benedek, Mohammed R. Milad, and Robert J. Ursano. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190457136.003.0017.

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Trauma and stress-related disorders make an excellent case for gene-environment interactions because although exposure to trauma and stress is a well-established risk factors toward their development, such factors alone are not sufficient to explain etiopathogenesis. Exposure to traumatic events is a prerequisite of posttraumatic stress disorder (PTSD) diagnosis, but the majority of individuals who are exposed to even a severe traumatic event do not develop PTSD. Why some individuals are vulnerable and others are resilient remains an open question. While genetic factors may play a significant

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Silvers, W. K. Coat Colors of Mice: A Model for Mammalian Gene Action and Interaction. Springer London, Limited, 2012.

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Han, Shihui. Gene-culture interaction on human behavior and the brain. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780198743194.003.0007.

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Chapter 7 reviews empirical findings that allow consideration of biological and environmental influences on human behavior from an evolutionary perspective (e.g., gene-culture coevolution) and from a perspective of individual development (e.g., gene-culture interaction). It also reviews imaging genetic studies that link genes with brain functional organization. It introduces a cultural neuroscience paradigm for investigating genetic influences on the coupling of brain activity and culture by presenting two studies that examined how serotonin transporter functional polymorphism and oxytocin rec

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Silvers, W. K. The Coat Colors of Mice: A Model For Mammalian Gene Action And Interaction. Springer, 2011.

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Book chapters on the topic "Gene-For-Gene interaction"

1

Cregan, P. B., M. J. Sadowsky, and H. H. Keyser. "Gene-for-gene interaction in the legume-Rhizobium symbiosis." In The Rhizosphere and Plant Growth. Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3336-4_32.

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Manohar, S. K., M. P. Gowrav, and H. V. Gangadharappa. "Materials for Gene Delivery Systems." In Interaction of Nanomaterials With Living Cells. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-2119-5_14.

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Xiong, Momiao, and Xuesen Wu. "Statistics for Testing Gene–Environment Interaction." In Environmental Factors, Genes, and the Development of Human Cancers. Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-6752-7_3.

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Turner, Stephen D., Scott M. Dudek, and Marylyn D. Ritchie. "Incorporating Domain Knowledge into Evolutionary Computing for Discovering Gene-Gene Interaction." In Parallel Problem Solving from Nature, PPSN XI. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15844-5_40.

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Kokošar, Jaka, Martin Špendl, and Blaž Zupan. "Gene Interactions in Survival Data Analysis: A Data-Driven Approach Using Restricted Mean Survival Time and Literature Mining." In Discovery Science. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-45275-8_20.

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AbstractUnveiling gene interactions is crucial for comprehending biological processes, particularly their combined impact on phenotypes. Computational methodologies for gene interaction discovery have been extensively studied, but their application to censored data has yet to be thoroughly explored. Our work introduces a data-driven approach to identifying gene interactions that profoundly influence survival rates through the use of survival analysis. Our approach calculates the restricted mean survival time (RMST) for gene pairs and compares it against their individual expressions. If the int

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Katagiri, Fumiaki, and R. Todd Leister. "Use of transient expression in plants for the study of the “gene-for-gene” interaction." In Cellular Integration of Signalling Pathways in Plant Development. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-642-72117-5_27.

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Bhalla, Parinishtha, Anukriti Verma, Bhawna Rathi, Shivani Sharda, and Pallavi Somvanshi. "Exploring Molecular Signatures in Spondyloarthritis: A Step Towards Early Diagnosis." In Proceedings of the Conference BioSangam 2022: Emerging Trends in Biotechnology (BIOSANGAM 2022). Atlantis Press International BV, 2022. http://dx.doi.org/10.2991/978-94-6463-020-6_15.

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AbstractSpondyloarthritis is an acute inflammatory disorder of the musculoskeletal system often accompanied by pain, stiffness, bone and tissue damage. It majorly consists of ankylosing spondylitis, psoriatic arthritis and reactive arthritis. It follows a differential diagnosis pattern for demarcation between the spondyloarthritis subtypes and other arthritic subtypes such as rheumatoid arthritis, juvenile arthritis and osteoarthritis due to the heterogeneity causing gradual chronicity and complications. Presence of definite molecular markers can not only improve diagnosis efficiency but also

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Miyao, Akio, and Hirohiko Hirochika. "Transposon-Insertion Lines of Rice for Analysis of Gene Function." In Rice Blast: Interaction with Rice and Control. Springer Netherlands, 2004. http://dx.doi.org/10.1007/978-0-306-48582-4_12.

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Da, Bingshui, Abhishek Gupta, Yew Soon Ong, and Liang Feng. "The Boon of Gene-Culture Interaction for Effective Evolutionary Multitasking." In Lecture Notes in Computer Science. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-28270-1_5.

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Tiwari, Aneeta, Elhan Khan, Sonam Dwivedi, Haram Sarfraz, and Iffat Zareen Ahmad. "Gene Regulation for Drought, Cold, Heavy Metal and Environmental Responses." In Genomics of Plant–Pathogen Interaction and the Stress Response. CRC Press, 2023. http://dx.doi.org/10.1201/9781003153481-9.

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Conference papers on the topic "Gene-For-Gene interaction"

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Le Borgne, S., J. M. Romero, H. A. Videla, J. M. Gonzalez, and C. Saiz-Jiménez. "Practical Cases of the Use of Molecular Techniques to Characterize Microbial Deterioration of Metallic Structures in Industry." In CORROSION 2007. NACE International, 2007. https://doi.org/10.5006/c2007-07523.

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Abstract Two specific cases of applying molecular techniques for deciphering the role of microorganisms in industrial processes are presented: an offshore seawater injection system and a wastewater treatment plant. In the first case, deoxyribonucleic acid (DNA) was extracted from a water sample taken from an offshore seawater injection system and from enrichment cultures from the same sample. The V3 hypervariable region of the 16S rDNA gene was amplified by the polymerase chain reaction (PCR) and bacterial diversity was studied using denaturing gel gradient electrophoresis (DGGE). DGGE monitor

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Zhu, Xiang Y., Alvin Ayala, Hetal Modi, and John J. Kilbane. "Application of Quantitative, Real-Time PCR in Monitoring Microbiologically-Influenced Corrosion (MIC) in Gas Pipelines." In CORROSION 2005. NACE International, 2005. https://doi.org/10.5006/c2005-05493.

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Abstract Quantitative PCR (qPCR) methods (fluorogenic 5′-nuclease assay and SYBR Green I assay) were developed to detect and quantify bacteria and some critical sub-populations related to gas and oil pipeline corrosion. 16S rRNA genes were targeted for the detection and quantification of total bacteria using fluorogenic 5′-nuclease assays. The functional genes, dissimilatory sulfite reductase gene (dsrAB), nitrite reductase gene (nirS), and methyl-coenzyme M reductase gene (mcrA), were targeted for sulfate reducing bacteria (SRB), denitrifying bacteria, and methanognes, respectively. The metho

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Diaz-Diaz, Norberto, Francisco Gomez-Vela, Jesus Aguilar-Ruiz, and Jorge Garcia-Gutierrez. "Gene-gene interaction based clustering method for microarray data." In 2011 11th International Conference on Intelligent Systems Design and Applications (ISDA). IEEE, 2011. http://dx.doi.org/10.1109/isda.2011.6121800.

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Assareh, Amin, L. Gwenn Volkert, and Jing Li. "Interaction Trees: Optimizing Ensembles of Decision Trees for Gene-Gene Interaction Detections." In 2012 Eleventh International Conference on Machine Learning and Applications (ICMLA). IEEE, 2012. http://dx.doi.org/10.1109/icmla.2012.114.

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Tong, Dong Ling, and Christine Siew Ken Lee. "A Systems Biology Approach to Model Gene-Gene Interaction for Childhood Sarcomas." In 2018 IEEE 18th International Conference on Bioinformatics and Bioengineering (BIBE). IEEE, 2018. http://dx.doi.org/10.1109/bibe.2018.00074.

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Li, Xin, Zhu Zhang, Hsinchun Chen, and Jiexun Li. "Graph Kernel-Based Learning for Gene Function Prediction from Gene Interaction Network." In 2007 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2007). IEEE, 2007. http://dx.doi.org/10.1109/bibm.2007.25.

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Huh, Iksoo, and Taesung Park. "Multifactor dimendionality reduction analysis for gene-gene interaction of multiple binary traits." In 2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2014. http://dx.doi.org/10.1109/bibm.2014.6999382.

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Gao, Li. "Gene-gene interaction networks for SYK in immune cell subsets for allergies and asthma." In ERS Congress 2024 abstracts. European Respiratory Society, 2024. http://dx.doi.org/10.1183/13993003.congress-2024.pa3077.

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Su, Ming-Wei, Kuan-Yen Tung, Ching-Hui Tsai, Nai-Wei Kuo, Pi-Hui Liang, and Yungling L. Lee. "GSTP1 Is A Hub Gene For Gene By Air Pollution Interaction On Childhood Asthma." In American Thoracic Society 2012 International Conference, May 18-23, 2012 • San Francisco, California. American Thoracic Society, 2012. http://dx.doi.org/10.1164/ajrccm-conference.2012.185.1_meetingabstracts.a2502.

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Alam, Md Ashad, Osamu Komori, Vince Calhoun, and Yu-Ping Wang. "Robust Kernel Canonical Correlation Analysis to Detect Gene-Gene Interaction for Imaging Genetics Data." In BCB '16: ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics. ACM, 2016. http://dx.doi.org/10.1145/2975167.2975196.

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Reports on the topic "Gene-For-Gene interaction"

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Sun, Jielin, Jianfeng Xu, and Siqun L. Zheng. Systematic Search for Gene-Gene Interaction Effect on Prostate Cancer Risk. Defense Technical Information Center, 2012. http://dx.doi.org/10.21236/ada564269.

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Sun, Jielin, Jianfeng Xu, and Siqun L. Zheng. Systematic Search for Gene-Gene Interaction Effect on Prostate Cancer Risk. Defense Technical Information Center, 2013. http://dx.doi.org/10.21236/ada593732.

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Tan, Qihua, Anatoli I. Yashin, Else M. Bladbjerg, et al. A case-only approach for assessing gene-sex interaction in human longevity. Max Planck Institute for Demographic Research, 2001. http://dx.doi.org/10.4054/mpidr-wp-2001-012.

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Torrungruang, Kitti, Soranun Chantarangsu, and Thanyachai Sura. Association between vitamin D receptor gene polymorphisms and chronic periodontitis in Thais. Chulalongkorn University, 2015. https://doi.org/10.58837/chula.res.2015.18.

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Polymorphisms of the vitamin D receptor (VDR) gene have been implicated in the susceptibility to infections and bone-related diseases. However, their relationship with periodontal disease remains unclear. This cross-sectional study investigated whether the susceptibility to chronic periodontitis in a Thai population is associated with VDR polymorphisms. Genomic DNA was obtained from 1,460 subjects, aged 39-65 years. Genotyping of VDR polymorphisms (FokI, BsmI, ApaI, and TaqI) was performed using real-time polymerase chain reaction. Subjects were categorized into three groups; no/mild, moderate

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Lifschitz, Eliezer, and Elliot Meyerowitz. The Relations between Cell Division and Cell Type Specification in Floral and Vegetative Meristems of Tomato and Arabidopsis. United States Department of Agriculture, 1996. http://dx.doi.org/10.32747/1996.7613032.bard.

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Meristems were the central issue of our project. Genes that are required for cell division, cell elongation, cell proliferation and cell fate were studied in the tomato system. The analysis of the dUTPase and threonine deaminase genes, along with the dissection of their regulatory regions is completed, while that of the RNR2 and PPO genes is at an advanced stage. All these genes were isolated in our laboratory. In addition, 8 different MADS box genes were studied in transgenic plants and their genetic relevances discovered. We have also shown that a given MADS box gene can modify the polarity

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Horwitz, Benjamin A., and Barbara Gillian Turgeon. Fungal Iron Acquisition, Oxidative Stress and Virulence in the Cochliobolus-maize Interaction. United States Department of Agriculture, 2012. http://dx.doi.org/10.32747/2012.7709885.bard.

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Our project focused on genes for high affinity iron acquisition in Cochliobolus heterostrophus, a necrotrophic pathogen of maize, and their intertwined relationship to oxidative stress status and virulence of the fungus on the host. An intriguing question was why mutants lacking the nonribosomal peptide synthetase (NRPS) gene (NPS6) responsible for synthesis of the extracellular siderophore, coprogen, are sensitive to oxidative stress. Our overall objective was to understand the mechanistic connection between iron stress and oxidative stress as related to virulence of a plant pathogen to its h

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Levisohn, Sharon, Mark Jackwood, and Stanley Kleven. New Approaches for Detection of Mycoplasma iowae Infection in Turkeys. United States Department of Agriculture, 1995. http://dx.doi.org/10.32747/1995.7612834.bard.

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Mycoplasma iowae (Mi) is a pathogenic avian mycoplasma which causes mortality in turkey embryos and as such has clinical and economic significance for the turkey breeder industry. Control of Mi infection is severely hampered by lack of adequate diagnostic tests, together with resistance to most antibiotics and resilience to environment. A markedly high degree of intra-species antigenic variation also contributes to difficulties in detection and control of infection. In this project we have designed an innovative gene-based diagnostic test based on specific amplification of the 16S rRNA gene of

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Barash, Itamar, J. Mina Bissell, Alexander Faerman, and Moshe Shani. Modification of Milk Composition via Transgenesis: The Role of the Extracellular Matrix in Regulating Transgene Expression. United States Department of Agriculture, 1995. http://dx.doi.org/10.32747/1995.7570558.bard.

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Altering milk composition via transgenesis depends on three main factors. (1) The availability of an efficient regulatory sequences for targeting transgene(s) to the mammary gland; (2) a reliable in vitro model to test the expression of transgenes prior to their introduction to the animal genome; and (3) better understanding of the major factors which determine the rate of gene expression and protein synthesis. The current studies provide the necessary means and knowledge to alter milk protein composition via transgenesis. The following specific goals were achieved: a: Identifying regulatory r

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Funkenstein, Bruria, and Shaojun (Jim) Du. Interactions Between the GH-IGF axis and Myostatin in Regulating Muscle Growth in Sparus aurata. United States Department of Agriculture, 2009. http://dx.doi.org/10.32747/2009.7696530.bard.

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Growth rate of cultured fish from hatching to commercial size is a major factor in the success of aquaculture. The normal stimulus for muscle growth in growing fish is not well understood and understanding the regulation of muscle growth in fish is of particular importance for aquaculture. Fish meat constitutes mostly of skeletal muscles and provides high value proteins in most people's diet. Unlike mammals, fish continue to grow throughout their lives, although the size fish attain, as adults, is species specific. Evidence indicates that muscle growth is regulated positively and negatively by

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Or, Etti, Tai-Ping Sun, Amnon Lichter, and Avichai Perl. Characterization and Manipulation of the Primary Components in Gibberellin Signaling in the Grape Berry. United States Department of Agriculture, 2010. http://dx.doi.org/10.32747/2010.7592649.bard.

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Abstract:

Seedless cultivars dominate the table grape industry. In these cultivars it is mandatory to apply gibberellin (GA) to stimulate berry development to a commercially acceptable size. These cultivars differ in their sensitivity to GA application, and it frequently results in adverse effects such as decreased bud fertility and increased fruit drop. Our long term goals are to (1) understand the molecular basis for the differential sensitivity and identify markers for selection of sensitive cultivars (2) to develop new strategies for targeted manipulation of the grape berry response to GA that will

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