Relevant bibliographies by topics / Protein families

Academic literature on the topic 'Protein families'

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Published: 4 June 2021
Last updated: 31 January 2023

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Journal articles on the topic "Protein families"

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Shewry, P., J. Jenkins, S. Griffiths-Jones, F. Beaudoin, and C. Mills. "Plant protein families." Biochemical Society Transactions 30, no. 5 (October 1, 2002): A107. http://dx.doi.org/10.1042/bst030a107b.

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Orengo, C. A., T. P. Flores, W. R. Taylor, and J. M. Thornton. "Identification and classification of protein fold families." "Protein Engineering, Design and Selection" 6, no. 5 (1993): 485–500. http://dx.doi.org/10.1093/protein/6.5.485.

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Chothia, Cyrus. "Protein families in the metazoan genome." Development 1994, Supplement (January 1, 1994): 27–33. http://dx.doi.org/10.1242/dev.1994.supplement.27.

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The evolution of development involves the development of new proteins. Estimates based on the initial results of the genome projects, and on the data banks of protein sequences and structures, suggest that the large majority of proteins come from no more than one thousand families. Members of a family are descended from a common ancestor. Protein families evolve by gene duplication and mutation. Mutations change the conformation of the peripheral regions of proteins; i.e. the regions that are involved, at least in part, in their function. If mutations proceed until only 20% of the residues in related proteins are identical, it is common for the conformational changes to affect half the structure. Most of the proteins involved in the interactions of cells, and in their assembly to form multicellular organisms, are mosaic proteins. These are large and have a modular structure, in that they are built of sets of homologous domains that are drawn from a relatively small number of protein families. Patthy's model for the evolution of mosaic proteins describes how they arose through the insertion of introns into genes, gene duplications and intronic recombination. The rates of progress in the genome sequencing projects, and in protein structure analyses, means that in a few years we will have a fairly complete outline description of the molecules responsible for the structure and function of organisms at several different levels of developmental complexity. This should make a major contribution to our understanding of the evolution of development.
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Altschuh, D., T. Vernet, P. Berti, D. Moras, and K. Nagai. "Coordinated amino acid changes in homologous protein families." "Protein Engineering, Design and Selection" 2, no. 3 (1988): 193–99. http://dx.doi.org/10.1093/protein/2.3.193.

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Hassell, J. R., J. H. Kimura, and V. C. Hascall. "Proteoglycan Core Protein Families." Annual Review of Biochemistry 55, no. 1 (June 1986): 539–67. http://dx.doi.org/10.1146/annurev.bi.55.070186.002543.

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Holm, Liisa. "Unification of protein families." Current Opinion in Structural Biology 8, no. 3 (June 1998): 372–79. http://dx.doi.org/10.1016/s0959-440x(98)80072-9.

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Buljan, Marija, and Alex Bateman. "The evolution of protein domain families." Biochemical Society Transactions 37, no. 4 (July 22, 2009): 751–55. http://dx.doi.org/10.1042/bst0370751.

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Protein domains are the common currency of protein structure and function. Over 10000 such protein families have now been collected in the Pfam database. Using these data along with animal gene phylogenies from TreeFam allowed us to investigate the gain and loss of protein domains. Most gains and losses of domains occur at protein termini. We show that the nature of changes is similar after speciation or duplication events. However, changes in domain architecture happen at a higher frequency after gene duplication. We suggest that the bias towards protein termini is largely because insertion and deletion of domains at most positions in a protein are likely to disrupt the structure of existing domains. We can also use Pfam to trace the evolution of specific families. For example, the immunoglobulin superfamily can be traced over 500 million years during its expansion into one of the largest families in the human genome. It can be shown that this protein family has its origins in basic animals such as the poriferan sponges where it is found in cell-surface-receptor proteins. We can trace how the structure and sequence of this family diverged during vertebrate evolution into constant and variable domains that are found in the antibodies of our immune system as well as in neural and muscle proteins.
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Boberg, Jorma, Tapio Salakoski, and Mauno Vihinen. "Representative selection of proteins based on nuclear families." "Protein Engineering, Design and Selection" 8, no. 5 (1995): 501–3. http://dx.doi.org/10.1093/protein/8.5.501.

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Liang, Ping, Bernard Labedan, and Monica Riley. "Physiological genomics of Escherichia coli protein families." Physiological Genomics 9, no. 1 (April 10, 2002): 15–26. http://dx.doi.org/10.1152/physiolgenomics.00086.2001.

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The well-researched Escherichia coli genome offers the opportunity to explore the value of using protein families within a single organism to enrich functional annotation procedures and to study mechanisms of protein evolution. Having identified multimodular proteins resulting from gene fusion, and treated each module as a separate protein, nonoverlapping sequence-similar families in E. coli could be assembled. Of 3,902 proteins of length 100 residues or more, 2,415 clustered into 609 protein families. The relatedness of function among members of each family was dissected in detail. Data on paralogous protein families provides valuable information in attributing putative function to unknown genes, supplementing existing function annotation. Enzymes, transporters, and regulators represent the three major types of proteins in E. coli. They are shown to have distinctive patterns in gene duplication and divergence and gene fusion, suggesting that details of protein evolution have been different for genes in these categories. Data for the complete list of paralogous protein families and updated functional annotation for E. coli K-12 are accessible in GenProtEC ( http://genprotec.mbl.edu ).
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Kumari, Rakhi, Nivedita Deo, and Pradeep Bhadola. "Random Matrix Analysis of Protein Families." ECS Transactions 107, no. 1 (April 24, 2022): 18877–91. http://dx.doi.org/10.1149/10701.18877ecst.

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Proteins are vital for almost all biochemical and cellular processes. Although there is an enormous growth in the protein sequence data, the statistical characterization, structure, and function of many of these sequences are still unknown. The statistical and spectral analysis of the Pearson correlation matrices between positions based on physiochemical properties of amino acids of seven protein families is performed and compared with the random Wishart matrix model results. A detailed analysis shows that the protein families significantly diverge from the Marcenko-Pastur distribution with many eigenvalues (outliers) outside the Wishart lower and upper bound. It is shown that level spacing distribution of protein families is similar to the Gaussian orthogonal ensemble. Further, the number variance varies as log of the system size indicating the presence of long range correlations within the protein families.
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Dissertations / Theses on the topic "Protein families"

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Abhiman, Saraswathi. "Prediction of function shift in protein families /." Stockholm, 2006. http://diss.kib.ki.se/2006/91-7140-869-X/.

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Biswas, Arpan Dinakarpandian Deendayal. "Complexity analysis of protein families." Diss., UMK access, 2004.

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Thesis (M.S.)--School of Computing and Engineering. University of Missouri--Kansas City, 2004.
"A thesis in computer science." Typescript. Advisor: Deendayal Dinakarpandian. Vita. Title from "catalog record" of the print edition Description based on contents viewed Feb. 22, 2006. Includes bibliographical references (leaves 60-62). Online version of the print edition.
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Elfving, Eric. "Automated annotation of protein families." Thesis, Linköpings universitet, Bioinformatik, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-69393.

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Introduction: The great challenge in bioinformatics is data integration. The amount of available data is always increasing and there are no common unified standards of where, or how, the data should be stored. The aim of this workis to build an automated tool to annotate the different member families within the protein superfamily of medium-chain dehydrogenases/reductases (MDR), by finding common properties among the member proteins. The goal is to increase the understanding of the MDR superfamily as well as the different member families.This will add to the amount of knowledge gained for free when a new, unannotated, protein is matched as a member to a specific MDR member family. Method: The different types of data available all needed different handling. Textual data was mainly compared as strings while numeric data needed some special handling such as statistical calculations. Ontological data was handled as tree nodes where ancestry between terms had to be considered. This was implemented as a plugin-based system to make the tool easy to extend with additional data sources of different types. Results: The biggest challenge was data incompleteness yielding little (or no) results for some families and thus decreasing the statistical significance of the results. Results show that all the human and mouse MDR members have a Pfam ADH domain (ADH_N and/or ADH_zinc_N) and takes part in an oxidation-reduction process, often with NAD or NADP as cofactor. Many of the proteins contain zinc and are expressed in liver tissue. Conclusions: A python based tool for automatic annotation has been created to annotate the different MDR member families. The tool is easily extendable to be used with new databases and much of the results agrees with information found in literature. The utility and necessity of this system, as well as the quality of its produced results, are expected to only increase over time, even if no additional extensions are produced, as the system itself is able to make further and more detailed inferences as more and more data become available.
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Rezvoy, Clément. "Large Scale Parallel Inference of Protein and Protein Domain families." Phd thesis, Ecole normale supérieure de lyon - ENS LYON, 2011. http://tel.archives-ouvertes.fr/tel-00682495.

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Protein domains are recurring independent segment of proteins. The combinatorial arrangement of domains is at the root of the functional and structural diversity of proteins. Several methods have been developed to infer protein domain decomposition and domain family clustering from sequence information alone. MkDom2 is one of those methods. Mkdom2 infers domain families in a greedy fashion. Families are inferred one after the other in order to create a delineation of domains on proteins and a clustering of those domains in families. MkDom2 is instrumental in the building of the ProDom database. The exponential growth of the number of sequences to process as rendered MkDom2 obsolete, it would now take several years to compute a newrelease of ProDom. We present a nous algorithm, MPI_MkDom2, allowing computation of several families at once across a distributed computing platform. MPI_MkDom2 is an asynchronous distributed algorithm managing load balancing to ensure efficient platform usage; it ensures the creation of a non-overlapping partitioning of the whole protein set. A new proximity measure is defined to assess the effect of the parallel computation on the result. We also Propose a second algorithm, MPI_mkDom3, allowing the simultaneous computation of a clustering of protein domains as well as full protein sharing the same domain decomposition.
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Stamler, Robin Jacob. "Structural biology of two proteins from two eye-related protein families : ABCR and TSP36." Thesis, Birkbeck (University of London), 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.414721.

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Sonnhammer, Erik Leonard Laage. "Classification of protein domain families for genomic sequence analysis." Thesis, Open University, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.336799.

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Kunin, Victor. "Evolution and function of protein families in complete genomes." Thesis, University of Cambridge, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.616101.

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Hill, E. E. "Evolution of protein families : genome sequences and three dimensional structures." Thesis, University of Cambridge, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.604054.

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The aim here is to investigate the relationship between sequence and structure for families of structurally related proteins with low sequence identity in order to determine any conserved positions and define them. We do this in two main ways: (i) Evolution of Three Dimensional Structures The members of the 4-helical cytokine superfamily of proteins have no significant sequence identity. Despite this superfamilies' low to non-existent sequence similarity their homology is inferred by their common structural and functions. We carry out an in depth analysis of the long and short chain families both separately and together to determine the conserved structural regions. From an examination of the residues that occur at equivalent sites within these regions we identified the only positions at which there is any conservation. We then determined the structural role of these conserved sites so as to understand how the members of this family can maintain similar structures but have very different sequences. (ii) Evolution of Sequences Within Genomes For the cadherin superfamily, we use automated methods and hand analysis (incorporating information gathered previously on the structurally important residues) in order to identify all cadherin domains in their respective proteins within two sequenced eukaryotic genomes, Caenorhabditis elegans and Drosophila melanogaster. Identification of the entire cadherin protein repertoires within the two eukaryotic genomes allowed us to carry out a comparative analysis. This allows that the cadherin repertoires in the two organisms are surprisingly different. The ability to identify all genes within an organism that encode certain structural domains is certainly a huge achievement, and must be part of the way towards understanding an organism in its entirety.
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Bonneau, Richard A. "Gene annotation using Ab initio protein structure prediction : method development and application to major protein families /." Thesis, Connect to this title online; UW restricted, 2001. http://hdl.handle.net/1773/9241.

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Daniels, Jan Peter. "Nuclear architecture and gene expression-associated protein families in trypanosoma brucei." Thesis, University of Oxford, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.509914.

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Books on the topic "Protein families"

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Orengo, Christine, and Alex Bateman, eds. Protein Families. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118743089.

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Land, Richard D. Real homeland security: How Godly families protect a nation. Nashville, Tenn: Broadman & Holman Publishers, 2003.

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The trap: A story to help protect families from pornography. Salt Lake City, Utah: Deseret Book, 2008.

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E, Angel Peter, and Herrlich Peter 1940-, eds. The fos and jun families of transcription factors. Boca Raton: CRC Press, 1994.

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Services, Montana Dept of Family. Building an adequate service system for children and families: Montana's opportunity to effectively protect children and strengthen families. Helena, Mont.]: The Dept., 1990.

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Network, Parenting in Africa, and International Child Support, eds. Strengthening families to protect children: Experiences and perspectives of professionals in Africa. Nairobi, Kenya: Parenting in Africa Network (PAN), Regional Office, ICS Africa and ICS, 2012.

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Quiénes nos protegen? Mankato, MN: Capstone Press, 2006.

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Fullerton, Don. Can pollution tax rebates protect low-income families?: The effects of relative wage rates. Cambridge, MA: National Bureau of Economic Research, 2010.

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Formas de morir y formas de vivir: El activismo contra la violencia policial. Ciudad Autónoma de Buenos Aires: Editores del Puerto, 2010.

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Aftab, Parry. A parent's guide to the Internet-- and how to protect your children in cyberspace. New York: SC Press, 1997.

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Book chapters on the topic "Protein families"

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Holm, Liisa, and Andreas Heger. "Automated Sequence-Based Approaches for Identifying Domain Families." In Protein Families, 1–24. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118743089.ch1.

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Baines, Anthony J. "Functional Adaptation and Plasticity in Cytoskeletal Protein Domains: Lessons from the Erythrocyte Model." In Protein Families, 237–84. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118743089.ch10.

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Rawlings, Neil D. "Unusual Species Distribution and Horizontal Transfer of Peptidases." In Protein Families, 285–314. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118743089.ch11.

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Wakabayashi, Steven T., Maksim A. Shlykov, Ujjwal Kumar, Vamsee S. Reddy, Ankur Malhotra, Erik L. Clarke, Jonathan S. Chen, et al. "Deducing Transport Protein Evolution Based on Sequence, Structure, and Function." In Protein Families, 315–39. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118743089.ch12.

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Makarova, Kira S., Daniel H. Haft, and Eugene V. Koonin. "CRISPR-Cas Systems and Cas Protein Families." In Protein Families, 341–81. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118743089.ch13.

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Charoensawan, Varodom, and Sarah Teichmann. "Families of Sequence-Specific DNA-Binding Domains in Transcription Factors across the Tree of Life." In Protein Families, 383–420. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118743089.ch14.

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Aravind, L., Vivek Anantharaman, Saraswathi Abhiman, and Lakshminarayan M. Iyer. "Evolution of Eukaryotic Chromatin Proteins and Transcription Factors." In Protein Families, 421–502. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118743089.ch15.

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Bateman, Alex. "Sequence Classification of Protein Families: Pfam and other Resources." In Protein Families, 25–36. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118743089.ch2.

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Cuff, Alison, Alexey Murzin, and Christine Orengo. "Classifying Proteins into Domain Structure Families." In Protein Families, 37–68. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118743089.ch3.

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Gough, Julian, Corin Yeats, and Christine Orengo. "Structural Annotations of Genomes with Superfamily and G3D." In Protein Families, 69–97. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118743089.ch4.

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Conference papers on the topic "Protein families"

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Tan, Jun, and Donald Adjeroh. "Predicting Protein Families using Protein Shape Context." In BCB'13: ACM-BCB2013. New York, NY, USA: ACM, 2013. http://dx.doi.org/10.1145/2506583.2512392.

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Bejerano, Gill, and Golan Yona. "Modeling protein families using probabilistic suffix trees." In the third annual international conference. New York, New York, USA: ACM Press, 1999. http://dx.doi.org/10.1145/299432.299445.

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Mukherjee, Saikat, Chang Zhao, and I. V. Ramakrishnan. "Profiling Protein Families from Partially Aligned Sequences." In Proceedings of the 2006 SIAM International Conference on Data Mining. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2006. http://dx.doi.org/10.1137/1.9781611972764.65.

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Thomas, John, Naren Ramakrishnan, and Chris Bailey-Kellogg. "Graphical models of residue coupling in protein families." In the 5th international workshop. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1134030.1134033.

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Kahn, Daniel, Clément Rezvoy, and Frédéric Vivien. "Parallel Large Scale Inference of Protein Domain Families." In 2008 14th IEEE International Conference on Parallel and Distributed Systems (ICPADS). IEEE, 2008. http://dx.doi.org/10.1109/icpads.2008.115.

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Mirkin, Boris, George Loizou, Paul Kellam, Renata Camargo, and Trevor Fenner. "Aggregating Homologous Protein Families in Evolutionary Reconstructions of Herpesviruses." In 2006 IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology. IEEE, 2006. http://dx.doi.org/10.1109/cibcb.2006.330944.

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Jiang Xie, Minchao Wang, Dongbo Dai, Huiran Zhang, and Wu Zhang. "A network clustering algorithm for detection of protein families." In 2012 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2012. http://dx.doi.org/10.1109/embc.2012.6347441.

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Aluru, Chaitanya, and Mona Singh. "Identifying Evolutionary Origins of Repeat Domains in Protein Families." In BCB '20: 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3388440.3412416.

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HUAN, J., W. WANG, A. WASHINGTON, J. PRINS, R. SHAH, and A. TROPSHA. "ACCURATE CLASSIFICATION OF PROTEIN STRUCTURAL FAMILIES USING COHERENT SUBGRAPH ANALYSIS." In Proceedings of the Pacific Symposium. WORLD SCIENTIFIC, 2003. http://dx.doi.org/10.1142/9789812704856_0039.

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MAGUITMAN, ANA G., ANDREAS RECHTSTEINER, KARIN VERSPOOR, CHARLIE E. STRAUSS, and LUIS M. ROCHA. "LARGE-SCALE TESTING OF BIBLIOME INFORMATICS USING PFAM PROTEIN FAMILIES." In Proceedings of the Pacific Symposium. WORLD SCIENTIFIC, 2005. http://dx.doi.org/10.1142/9789812701626_0008.

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Reports on the topic "Protein families"

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Matthews, Lisa, Guanming Wu, Robin Haw, Timothy Brunson, Nasim Sanati, Solomon Shorser, Deidre Beavers, Patrick Conley, Lincoln Stein, and Peter D'Eustachio. Illuminating Dark Proteins using Reactome Pathways. Reactome, October 2022. http://dx.doi.org/10.3180/poster/20221027matthews.

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Diseases are often the consequence of proteins or protein complexes that are non-functional or that function improperly. An active area of research has focused on the identification of molecules that can interact with defective proteins and restore their function. While 22% percent of human proteins are estimated to be druggable, less than fifteen percent are targeted by FDA-approved drugs, and the vast majority of untargeted proteins are understudied or so-called "dark" proteins. Elucidation of the function of these dark proteins, particularly those in commonly drug-targeted protein families, may offer therapeutic opportunities for many diseases. Reactome is the most comprehensive, open-access pathway knowledgebase covering 2585 pathways and including 14246 reactions, 11088 proteins, 13984 complexes, and 1093 drugs. Placing dark proteins in the context of Reactome pathways provides a framework of reference for these proteins facilitating the generation of hypotheses for experimental biologists to develop targeted experiments, unravel the potential functions of these proteins, and then design drugs to manipulate them. To this end, we have trained a random forest with 106 protein/gene pairwise features collected from multiple resources to predict functional interactions between dark proteins and proteins annotated in Reactome and then developed three scores to measure the interactions between dark proteins and Reactome pathways based on enrichment analysis and fuzzy logic simulations. Literature evidence via manual checking and systematic NLP-based analysis support predicted interacting pathways for dark proteins. To visualize dark proteins in the context of Reactome pathways, we have also developed a new website, idg.reactome.org, by extending the Reactome web application with new features illustrating these proteins together with tissue-specific protein and gene expression levels and drug interactions.
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Weller, Joel, Harris Lewin, Micha Ron, and George Wiggans. Detection and Mapping of Genes Affecting Traits of Economic Importance in Dairy Cattle with the Aid of Molecular Genetic Markers. United States Department of Agriculture, December 1995. http://dx.doi.org/10.32747/1995.7613024.bard.

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Forty-seven poly-TG microsatellites were developed at the U of IL, and 11 genetic markers were developed at ARO, nine of which were poly-AGC microsatellites. Markers were typed on the reference families of CSIRO, Australia; GRANADA, Texas; and IRRF, Illinois, for chromosome assignment and linkage mapping. Nine North American al organizations contributed semen to the Dairy Bull DNA Repository (DBDR), which currently has 65,743 units from 3366 bulls. Semen was obtained for 31 out of 35 grandsires. Semen of 28 and 23 sons of two Israeli bulls was also collected. Eighteen grandsires were genotyped for 75 microsatellites. One thousand, three hundred and sixty-two sons with evaluation from 17 families were genotyped for 24 markers. Eleven thousand, six hundred and twenty sons genotypes were determined, of which 8,802 were informative. The genotype data was matched to the bulls' daughter yield deviations (DYD) for seven traits; milk, fat, and protein production; fat and protein percent; somatic cell concentration (SCS); and productive herd life. Seven loci had significant effects at p<0.05, but only two loci, TGLA263 and MGTG7, had significant effects at p<0.01, and the effect of TGLA263 on fat percentage was significant at p<0.0001. There was at least one significant effect for each of the seven traits analyzed.
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Ghanim, Murad, Joe Cicero, Judith K. Brown, and Henryk Czosnek. Dissection of Whitefly-geminivirus Interactions at the Transcriptomic, Proteomic and Cellular Levels. United States Department of Agriculture, February 2010. http://dx.doi.org/10.32747/2010.7592654.bard.

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Our project focuses on gene expression and proteomics of the whitefly Bemisia tabaci (Gennadius) species complex in relation to the internal anatomy and localization of expressed genes and virions in the whitefly vector, which poses a major constraint to vegetable and fiber production in Israel and the USA. While many biological parameters are known for begomovirus transmission, nothing is known about vector proteins involved in the specific interactions between begomoviruses and their whitefly vectors. Identifying such proteins is expected to lead to the design of novel control methods that interfere with whitefly-mediated begomovirus transmission. The project objectives were to: 1) Perform gene expression analyses using microarrays to study the response of whiteflies (B, Q and A biotypes) to the acquisition of begomoviruses (Tomato yellow leaf curl (TYLCV) and Squash leaf curl (SLCV). 2) Construct a whitefly proteome from whole whiteflies and dissected organs after begomovirus acquisition. 3) Validate gene expression by q-RTPCR and sub-cellular localization of candidate ESTs identified in microarray and proteomic analyses. 4) Verify functionality of candidate ESTs using an RNAi approach, and to link these datasets to overall functional whitefly anatomical studies. During the first and second years biological experiments with TYLCV and SLCV acquisition and transmission were completed to verify the suitable parameters for sample collection for microarray experiments. The parameters were generally found to be similar to previously published results by our groups and others. Samples from whole whiteflies and midguts of the B, A and Q biotypes that acquired TYLCV and SLCV were collected in both the US and Israel and hybridized to B. tabaci microarray. The data we analyzed, candidate genes that respond to both viruses in the three tested biotypes were identified and their expression that included quantitative real-time PCR and co-localization was verified for HSP70 by the Israeli group. In addition, experiments were undertaken to employ in situ hybridization to localize several candidate genes (in progress) using an oligonucleotide probe to the primary endosymbiont as a positive control. A proteome and corresponding transcriptome to enable more effective protein identification of adult whiteflies was constructed by the US group. Further validation of the transmission route of begomoviruses, mainly SLCV and the involvement of the digestive and salivary systems was investigated (Cicero and Brown). Due to time and budget constraints the RNAi-mediated silencing objective to verify gene function was not accomplished as anticipated. HSP70, a strong candidate protein that showed over-expression after TYLCV and SLCV acquisition and retention by B. tabaci, and co-localization with TYLCV in the midgut, was further studies. Besides this protein, our joint research resulted in the identification of many intriguing candidate genes and proteins that will be followed up by additional experiments during our future research. To identify these proteins it was necessary to increase the number and breadth of whitefly ESTs substantially and so whitefly cDNAs from various libraries made during the project were sequenced (Sanger, 454). As a result, the proteome annotation (ID) was far more successful than in the initial attempt to identify proteins using Uniprot or translated insect ESTs from public databases. The extent of homology shared by insects in different orders was surprisingly low, underscoring the imperative need for genome and transcriptome sequencing of homopteran insects. Having increased the number of EST from the original usable 5500 generated several years ago to >600,000 (this project+NCBI data mining), we have identified about one fifth of the whitefly proteome using these new resources. Also we have created a database that links all identified whitefly proteins to the PAVEdb-ESTs in the database, resulting in a useful dataset to which additional ESTS will be added. We are optimistic about the prospect of linking the proteome ID results to the transcriptome database to enable our own and other labs the opportunity to functionally annotate not only genes and proteins involved in our area of interest (whitefly mediated transmission) but for the plethora of other functionalities that will emerge from mining and functionally annotating other key genes and gene families in whitefly metabolism, development, among others. This joint grant has resulted in the identification of numerous candidate proteins involved in begomovirus transmission by B. tabaci. A next major step will be to capitalize on validated genes/proteins to develop approaches to interfere with the virus transmission.
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4

Weller, Joel I., Harris A. Lewin, and Micha Ron. Determination of Allele Frequencies for Quantitative Trait Loci in Commercial Animal Populations. United States Department of Agriculture, February 2005. http://dx.doi.org/10.32747/2005.7586473.bard.

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Individual loci affecting economic traits in dairy cattle (ETL) have been detected via linkage to genetic markers by application of the granddaughter design in the US population and the daughter design in the Israeli population. From these analyses it is not possible to determine allelic frequencies in the population at large, or whether the same alleles are segregating in different families. We proposed to answer this question by application of the "modified granddaughter design", in which granddaughters with a common maternal grandsire are both genotyped and analyzed for the economic traits. The objectives of the proposal were: 1) to fine map three segregating ETL previously detected by a daughter design analysis of the Israeli dairy cattle population; 2) to determine the effects of ETL alleles in different families relative to the population mean; 3) for each ETL, to determine the number of alleles and allele frequencies. The ETL on Bostaurusautosome (BT A) 6 chiefly affecting protein concentration was localized to a 4 cM chromosomal segment centered on the microsatellite BM143 by the daughter design. The modified granddaughter design was applied to a single family. The frequency of the allele increasing protein percent was estimated at 0.63+0.06. The hypothesis of equal allelic frequencies was rejected at p<0.05. Segregation of this ETL in the Israeli population was confirmed. The genes IBSP, SPP1, and LAP3 located adjacent to BM143 in the whole genome cattle- human comparative map were used as anchors for the human genome sequence and bovine BAC clones. Fifteen genes within 2 cM upstream of BM143 were located in the orthologous syntenic groups on HSA4q22 and HSA4p15. Only a single gene, SLIT2, was located within 2 cM downstream of BM143 in the orthologous HSA4p15 region. The order of these genes, as derived from physical mapping of BAC end sequences, was identical to the order within the orthologous syntenic groups on HSA4: FAM13A1, HERC3. CEB1, FLJ20637, PP2C-like, ABCG2, PKD2. SPP, MEP, IBSP, LAP3, EG1. KIAA1276, HCAPG, MLR1, BM143, and SLIT2. Four hundred and twenty AI bulls with genetic evaluations were genotyped for 12 SNPs identified in 10 of these genes, and for BM143. Seven SNPs displayed highly significant linkage disequilibrium effects on protein percentage (P<0.000l) with the greatest effect for SPP1. None of SNP genotypes for two sires heterozygous for the ETL, and six sires homozygous for the ETL completely corresponded to the causative mutation. The expression of SPP 1 and ABCG2 in the mammary gland corresponded to the lactation curve, as determined by microarray and QPCR assays, but not in the liver. Anti-sense SPP1 transgenic mice displayed abnormal mammary gland differentiation and milk secretion. Thus SPP 1 is a prime candidate gene for this ETL. We confirmed that DGAT1 is the ETL segregating on BTA 14 that chiefly effects fat concentration, and that the polymorphism is due to a missense mutation in an exon. Four hundred Israeli Holstein bulls were genotyped for this polymorphism, and the change in allelic frequency over the last 20 years was monitored.
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5

Fluhr, Robert, and Maor Bar-Peled. Novel Lectin Controls Wound-responses in Arabidopsis. United States Department of Agriculture, January 2012. http://dx.doi.org/10.32747/2012.7697123.bard.

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Innate immune responses in animals and plants involve receptors that recognize microbe-associated molecules. In plants, one set of this defense system is characterized by large families of TIR–nucleotide binding site–leucine-rich repeat (TIR-NBS-LRR) resistance genes. The direct interaction between plant proteins harboring the TIR domain with proteins that transmit and facilitate a signaling pathway has yet to be shown. The Arabidopsis genome encodes TIR-domain containing genes that lack NBS and LRR whose functions are unknown. Here we investigated the functional role of such protein, TLW1 (TIR LECTIN WOUNDRESPONSIVE1). The TLW1 gene encodes a protein with two domains: a TIR domain linked to a lectin-containing domain. Our specific aim in this proposal was to examine the ramifications of the TL1-glycan interaction by; A) The functional characterization of TL1 activity in the context of plant wound response and B) Examine the hypothesis that wounding induced specific polysaccharides and examine them as candidates for TL-1 interactive glycan compounds. The Weizmann group showed TLW1 transcripts are rapidly induced by wounding in a JA-independent pathway and T-DNA-tagged tlw1 mutants that lack TLW1 transcripts, fail to initiate the full systemic wound response. Transcriptome methodology analysis was set up and transcriptome analyses indicates a two-fold reduced level of JA-responsive but not JA-independent transcripts. The TIR domain of TLW1 was found to interact directly with the KAT2/PED1 gene product responsible for the final b-oxidation steps in peroxisomal-basedJA biosynthesis. To identify potential binding target(s) of TL1 in plant wound response, the CCRC group first expressed recombinant TL1 in bacterial cells and optimized conditions for the protein expression. TL1 was most highly expressed in ArcticExpress cell line. Different types of extraction buffers and extraction methods were used to prepare plant extracts for TL1 binding assay. Optimized condition for glycan labeling was determined, and 2-aminobenzamide was used to label plant extracts. Sensitivity of MALDI and LC-MS using standard glycans. THAP (2,4,6- Trihydroxyacetophenone) showed minimal background peaks at positive mode of MALDI, however, it was insensitive with a minimum detection level of 100 ng. Using LC-MS, sensitivity was highly increased enough to detect 30 pmol concentration. However, patterns of total glycans displayed no significant difference between different extraction conditions when samples were separated with Dionex ICS-2000 ion chromatography system. Transgenic plants over-expressing lectin domains were generated to obtain active lectin domain in plant cells. Insertion of the overexpression construct into the plant genome was confirmed by antibiotic selection and genomic DNA PCR. However, RT-PCR analysis was not able to detect increased level of the transcripts. Binding ability of azelaic acid to recombinant TL1. Azelaic acid was detected in GST-TL1 elution fraction, however, DHB matrix has the same mass in background signals, which needs to be further tested on other matrices. The major findings showed the importance of TLW1 in regulating wound response. The findings demonstrate completely novel and unexpected TIR domain interactions and reveal a control nexus and mechanism that contributes to the propagation of wound responses in Arabidopsis. The implications are to our understanding of the function of TIR domains and to the notion that early molecular events occur systemically within minutes of a plant sustaining a wound. A WEB site (http://genome.weizmann.ac.il/hormonometer/) was set up that enables scientists to interact with a collated plant hormone database.
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6

Weller, Joel, Harris Lewin, Micha Ron, George Wiggans, and Paul VanRaden. A Systematic Genome Search for Genes Affecting Economic Traits Dairy Cattle with the Aid of Genetic Markers. United States Department of Agriculture, April 1999. http://dx.doi.org/10.32747/1999.7695836.bard.

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The objectives were to continue collection of semen for the US dairy bull DNA repository, to conduct a systematic search of the Holstein genome for economically significant economic trait loci (ETL), to develop and refine statistical techniques for the analysis of the data generated, and to confirm significant effects by genotyping daughters i Israel and additional US sons. One-thousand-seventy-six sons of eight US grandsires were genotyped for 174 microsatellites located on all 29 autosomes. ETL were detected for milk production traits on seven chromosomes. ETL for milk and fat yield and fat and protein percentage on BTA3 was mapped to between the markers BL41 and TGLA263. The 95% confidence interval for the ETL affecting fat percentage on BTA14 localized this ETL between the contromere and chromosome position 11 cM. This ETL was verified in the Israeli cattle population by genotyping an independent sample of cows from seven families. The radiation hybrid data for the centromeric region of BTA14 is defined by a single linkage group. Order of Type I genes within this region, CYC-FADK-TG-SQLE, is conserved between human and cattle. Thus, HSA8, the human homologue of BTA14, can be used to identify candidate genes for the ETL.
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7

Crisosto, Carlos, Susan Lurie, Haya Friedman, Ebenezer Ogundiwin, Cameron Peace, and George Manganaris. Biological Systems Approach to Developing Mealiness-free Peach and Nectarine Fruit. United States Department of Agriculture, 2007. http://dx.doi.org/10.32747/2007.7592650.bard.

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Peach and nectarine production worldwide is increasing; however consumption is flat or declining because of the inconsistent eating quality experienced by consumers. The main factor for this inconsistent quality is mealiness or woolliness, a form of chilling injury that develops following shipping periods in the global fruit market today. Our research groups have devised various postharvest methods to prolong storage life, including controlled atmosphere and delayed storage; however, these treatments only delay mealiness. Mealiness texture results from disruption of the normal ripening process involving disassembly of cell wall material, and creates a soft fruit texture that is dry and grainy instead of juicy and smooth. Solving this problem is a prerequisite for increasing the demand for fresh peach and nectarine. Two approaches were used to reveal genes and their associated biochemical processes that can confer resistance to mealiness or wooliness. At the Volcani Center, Israel, a nectarine cultivar and the peach cultivar (isogenetic materials) from which the nectarine cultivar spontaneously arose, and at the Kearney Agricultural Center of UC Davis, USA, a peach population that segregates for quantitative resistance to mealiness was used for dissecting the genetic components of mealiness development. During our project we have conducted research integrating the information from phenotypic, biochemical and gene expression studies, proposed possible candidate genes and SNPs-QTLs mapping that are involved in reducing peach mealiness susceptibility. Numerous genes related to ethylene biosynthesis and its signal transduction, cell wall structure and metabolism, stress response, different transcription factor families were detected as being differentially accumulated in the cold-treated samples of these sensitive and less sensitive genotypes. The ability to produce ethylene and keep active genes involved in ethylene signaling, GTP-binding protein, EIN-3 binding protein and an ethylene receptor and activation of ethyleneresponsive fruit ripening genes during cold storage provided greater resistance to CI. Interestingly, in the functional category of genes differentially expressed at harvest, less chilling sensitive cultivar had more genes in categories related to antioxidant and heat sock proteins/chaperones that may help fruit to adapt to low temperature stress. The specific objectives of the proposed research were to: characterize the phenotypes and cell wall components of the two resistant systems in response to mealiness- inducing conditions; identify commonalities and specific differences in cell wall proteins and the transcriptome that are associated with low mealiness incidence; integrate the information from phenotypic, biochemical, and gene expression studies to identify candidate genes that are involved in reducing mealiness susceptibility; locate these genes in the Prunus genome; and associate the genes with genomic regions conferring quantitative genetic variation for mealiness resistance. By doing this we will locate genetic markers for mealiness development, essential tools for selection of mealiness resistant peach lines with improved fruit storability and quality. In our research, QTLs have been located in our peach SNPs map, and proposed candidate genes obtained from the integrated result of phenotypic, biochemical and gene expression analysis are being identified in our QTLs as an approach searching for consistent assistant markers for peach breeding programs.
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8

Fullerton, Don, and Holly Monti. Can Pollution Tax Rebates Protect Low-Income Families? The Effects of Relative Wage Rates. Cambridge, MA: National Bureau of Economic Research, April 2010. http://dx.doi.org/10.3386/w15935.

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9

Manulis, Shulamit, Christine D. Smart, Isaac Barash, Guido Sessa, and Harvey C. Hoch. Molecular Interactions of Clavibacter michiganensis subsp. michiganensis with Tomato. United States Department of Agriculture, January 2011. http://dx.doi.org/10.32747/2011.7697113.bard.

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Clavibacter michiganensis subsp. michiganensis (Cmm), the causal agent of bacterial wilt and canker of tomato, is the most destructive bacterial disease of tomato causing substantial economic losses in Israel, the U.S.A. and worldwide. The molecular strategies that allow Cmm, a Gram-positive bacterium, to develop a successful infection in tomato plants are largely unknown. The goal of the project was to elucidate the molecular interactions between Cmmand tomato. The first objective was to analyze gene expression profiles of susceptible tomato plants infected with pathogenic and endophytic Cmmstrains. Microarray analysis identified 122 genes that were differentially expressed during early stages of infection. Cmm activated typical basal defense responses in the host including induction of defense-related genes, production of scavenging of free oxygen radicals, enhanced protein turnover and hormone synthesis. Proteomic investigation of the Cmm-tomato interaction was performed with Multi-Dimensional Protein Identification Technology (MudPIT) and mass spectroscopy. A wide range of enzymes secreted by Cmm382, including cell-wall degrading enzymes and a large group of serine proteases from different families were identified in the xylem sap of infected tomato. Based on proteomic results, the expression pattern of selected bacterial virulence genes and plant defense genes were examined by qRT-PCR. Expression of the plasmid-borne cellulase (celA), serine protease (pat-1) and serine proteases residing on the chp/tomA pathogenicity island (chpCandppaA), were significantly induced within 96 hr after inoculation. Transcription of chromosomal genes involved in cell wall degradation (i.e., pelA1, celB, xysA and xysB) was also induced in early infection stages. The second objective was to identify by VIGS technology host genes affecting Cmm multiplication and appearance of disease symptoms in plant. VIGS screening showed that out of 160 tomato genes, which could be involved in defense-related signaling, suppression of 14 genes led to increase host susceptibility. Noteworthy are the genes Snakin-2 (inhibitor of Cmm growth) and extensin-like protein (ELP) involved in cell wall fortification. To further test the significance of Snakin -2 and ELP in resistance towards Cmm, transgenic tomato plants over-expressing the two genes were generated. These plants showed partial resistance to Cmm resulting in a significant delay of the wilt symptoms and reduction in size of canker lesion compared to control. Furthermore, colonization of the transgenic plants was significantly lower. The third objective was to assess the involvement of ethylene (ET), jasmonate (JA) and salicylic acid (SA) in Cmm infection. Microarray and proteomic studies showed the induction of enzymes involved in ET and JA biosynthesis. Cmm promoted ET production 8 days after inoculation and SIACO, a key enzyme of ET biosynthesis, was upregulated. Inoculation of the tomato mutants Never ripe (Nr) impaired in ET perception and transgenic plants with reduced ET synthesis significantly delayed wilt symptoms as compared to the wild-type plants. The retarded wilting in Nr plants was shown to be a specific effect of ET insensitivity and was not due to altered expression of defense related genes, reduced bacterial population or decrease in ethylene biosynthesis . In contrast, infection of various tomato mutants impaired in JA biosynthesis (e.g., def1, acx1) and JA insensitive mutant (jai1) yielded unequivocal results. The fourth objective was to determine the role of cell wall degrading enzymes produced by Cmm in xylem colonization and symptoms development. A significance increase (2 to 7 fold) in expression of cellulases (CelA, CelB), pectate lyases (PelA1, PelA2), polygalacturonase and xylanases (XylA, XylB) was detected by qRT-PCR and by proteomic analysis of the xylem sap. However, with the exception of CelA, whose inactivation led to reduced wilt symptoms, inactivation of any of the other cell wall degrading enzymes did not lead to reduced virulence. Results achieved emphasized the complexity involved in Cmm-tomato interactions. Nevertheless they provide the basis for additional research which will unravel the mechanism of Cmm pathogenicity and formulating disease control measures.
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10

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, March 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 a variety of growth and transcription factors that control both muscle cell proliferation and differentiation. In particular, growth hormone (GH), fibroblast growth factors (FGFs), insulin-like growth factors (IGFs) and transforming growth factor-13 (TGF-13) play critical roles in myogenesis during animal growth. An important advance in our understanding of muscle growth was provided by the recent discovery of the crucial functions of myostatin (MSTN) in controlling muscle growth. MSTN is a member of the TGF-13 superfamily and functions as a negative regulator of skeletal muscle growth in mammals. Studies in mammals also provided evidence for possible interactions between GH, IGFs, MSTN and the musclespecific transcription factor My oD with regards to muscle development and growth. The goal of our project was to try to clarify the role of MSTNs in Sparus aurata muscle growth and in particular determine the possible interaction between the GH-IGFaxis and MSTN in regulating muscle growth in fish. The steps to achieve this goal included: i) Determining possible relationship between changes in the expression of growth-related genes, MSTN and MyoD in muscle from slow and fast growing sea bream progeny of full-sib families and that of growth rate; ii) Testing the possible effect of over-expressing GH, IGF-I and IGF-Il on the expression of MSTN and MyoD in skeletal muscle both in vivo and in vitro; iii) Studying the regulation of the two S. aurata MSTN promoters and investigating the possible role of MyoD in this regulation. The major findings of our research can be summarized as follows: 1) Two MSTN promoters (saMSTN-1 and saMSTN-2) were isolated and characterized from S. aurata and were found to direct reporter gene activity in A204 cells. Studies were initiated to decipher the regulation of fish MSTN expression in vitro using the cloned promoters; 2) The gene coding for saMSTN-2 was cloned. Both the promoter and the first intron were found to be polymorphic. The first intron zygosity appears to be associated with growth rate; 3) Full length cDNA coding for S. aurata growth differentiation factor-l I (GDF-II), a closely related growth factor to MSTN, was cloned from S. aurata brain, and the mature peptide (C-terminal) was found to be highly conserved throughout evolution. GDF-II transcript was detected by RT -PCR analysis throughout development in S. aurata embryos and larvae, suggesting that this mRNA is the product of the embryonic genome. Transcripts for GDF-Il were detected by RT-PCR in brain, eye and spleen with highest level found in brain; 4) A novel member of the TGF-Bsuperfamily was partially cloned from S. aurata. It is highly homologous to an unidentified protein (TGF-B-like) from Tetraodon nigroviridisand is expressed in various tissues, including muscle; 5) Recombinant S. aurata GH was produced in bacteria, refolded and purified and was used in in vitro and in vivo experiments. Generally, the results of gene expression in response to GH administration in vivo depended on the nutritional state (starvation or feeding) and the time at which the fish were sacrificed after GH administration. In vitro, recombinantsaGH activated signal transduction in two fish cell lines: RTHI49 and SAFI; 6) A fibroblastic-like cell line from S. aurata (SAF-I) was characterized for its gene expression and was found to be a suitable experimental system for studies on GH-IGF and MSTN interactions; 7) The gene of the muscle-specific transcription factor Myogenin was cloned from S. aurata, its expression and promoter activity were characterized; 8) Three genes important to myofibrillogenesis were cloned from zebrafish: SmyDl, Hsp90al and skNAC. Our data suggests the existence of an interaction between the GH-IGFaxis and MSTN. This project yielded a great number of experimental tools, both DNA constructs and in vitro systems that will enable further studies on the regulation of MSTN expression and on the interactions between members of the GHIGFaxis and MSTN in regulating muscle growth in S. aurata.
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