Renewal is sought for a Program Project in statistical and quantitative genetics at North Carolina State University, with subcontracts to the University of California at Davis, and oklahoma State University. The objectives of the proposal are to conduct research in statistical and quantitative genetics, with an ultimate goal of developing a methodology for understanding the genetic basis of complex characters, and the evolution of such characters and of molecular sequences. The program consists of eight projects, the first of which is an administrative core. This provides administrative, computing and statistical services to the other projects and maintains communication among all projects. Three projects are housed within the Department of Statistics. One is concerned with methodology for the location of human disease genes and the use of DNA markers for individual identification. A second develops methods for using information from genetic maps to locate genes affecting quantitative traits. The composite interval mapping method will be extended to outbred populations. The third establishes statistical methods for characterizing variation of preferred residues among sequence sites, and looks at the interplay between protein secondary structure and evolution. Two projects are within the Department of Genetics. One concerns a unified theory for the development and evolution of complex morphological structures. The evolution of transcription factors will be studied, and rates of development early and late in postnatal ontogeny of the mouse will be characterized. The other uses the model of bristle number in Drosophila to determine the genetic basis of quantitative variation in phenotypes in terms of additive, dominance, pleiotropic and epistatic effects of alleles at individual quantitative trait loci. The project in the Department of Animal Science is on the genetic basis of obesity in the mouse. Genes responsible for the trait will be mapped, with an emphasis on the effects of environmental factors such as diet. The Forestry Department project will locate genes responsible for lignin content in pine, and compare these genes with those known to control activity of enzymes in the monlignol biosynthetic pathway.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Program Projects (P01)
Project #
5P01GM045344-07
Application #
2022435
Study Section
Special Emphasis Panel (ZRG7-SSS-8 (08))
Project Start
1990-12-01
Project End
2000-11-30
Budget Start
1996-12-01
Budget End
1997-11-30
Support Year
7
Fiscal Year
1997
Total Cost
Indirect Cost
Name
North Carolina State University Raleigh
Department
Biostatistics & Other Math Sci
Type
Schools of Arts and Sciences
DUNS #
City
Raleigh
State
NC
Country
United States
Zip Code
27695
Bryant, David; Bouckaert, Remco; Felsenstein, Joseph et al. (2012) Inferring species trees directly from biallelic genetic markers: bypassing gene trees in a full coalescent analysis. Mol Biol Evol 29:1917-32
RoyChoudhury, Arindam; Thompson, Elizabeth A (2012) Ascertainment correction for a population tree via a pruning algorithm for likelihood computation. Theor Popul Biol 82:59-65
Beecham, Gary W; Weir, Bruce S (2011) Confidence interval of the likelihood ratio associated with mixed stain DNA evidence. J Forensic Sci 56 Suppl 1:S166-71
Magwire, Michael M; Yamamoto, Akihiko; Carbone, Mary Anna et al. (2010) Quantitative and molecular genetic analyses of mutations increasing Drosophila life span. PLoS Genet 6:e1001037
Gao, Xiaoyi; Martin, Eden R (2009) Using allele sharing distance for detecting human population stratification. Hum Hered 68:182-91
Funk-Keenan, Jhondra; Haire, Frances; Woolard, Sara et al. (2008) Hepatic endopolyploidy as a cellular consequence of age-specific selection for rate of development in mice. J Exp Zool B Mol Dev Evol 310:385-97
Kim, Yunjung; Feng, Sheng; Zeng, Zhao-Bang (2008) Measuring and partitioning the high-order linkage disequilibrium by multiple order Markov chains. Genet Epidemiol 32:301-12
Fernandes, Andrew D; Atchley, William R (2008) Site-specific evolutionary rates in proteins are better modeled as non-independent and strictly relative. Bioinformatics 24:2177-83
Aylor, David L; Zeng, Zhao-Bang (2008) From classical genetics to quantitative genetics to systems biology: modeling epistasis. PLoS Genet 4:e1000029
Garcia, Antonio Augusto Franco; Wang, Shengchu; Melchinger, Albrecht E et al. (2008) Quantitative trait loci mapping and the genetic basis of heterosis in maize and rice. Genetics 180:1707-24

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