SAES-422 Multistate Research Activity Accomplishments Report
Sections
Status: Approved
Basic Information
- Project No. and Title: NCCC_OLD204 : The Interface of Molecular and Quantitative Genetics in Plant and Animal Breeding
- Period Covered: 02/01/2003 to 02/01/2004
- Date of Report: 08/05/2004
- Annual Meeting Dates: 02/12/2004 to 02/13/2004
Participants
Bastiaansen, John (john.bastiaansen@sygeninternational.com)- Sygen; Deeb, Nader (nader.deeb@pic.com) - Sygen; Dentine, Margaret (mrdentine@cals.wisc.edu) - Univ. of Wisconsin; Fernando, Rohan (rohan@iastate.edu) - Iowa State; Grignola, Fernando (fernando.e.grignola@monsanto.com)- Monsanto; Henderson, David (dnadave@u.arizona.edu) - Univ. of Arizona; Jannink, Jean-Luc (jjannink@iastate.edu) - Iowa State; Kinghorn, Brian (brian.kinghorn@sygeninternational.com) - Sygen; Misztal, Ignacy (ignacy@uga.edu) - Univ. of Georgia; Muir, Bill (bmuir@purdue.edu) - Purdue Univ.; Rocha, John (john.rocha@sygeninternational.com) - Sygen; Romero-Severson, Jeanne (romeros@fnr.purdue.edu) - Purdue Univ.; Rosa, Guilherme (rosag@msu.edu) - Michigan State; Thro, Anne Marie (athro@csrees.usda.gov) - USDA/CSREES; van der Steen, Hein (hein.vandersteen@sygeninternational.com) - Sygen; Xu, Shizhong (xu@genetics.usr.edu) - UC Riverside; Yu, Nan (nan.yu@sygeninternational.com) - Sygen; Non-attending stations in 2004: Arkansas, Kotswold, Dow, Illinois, Minnesota, Nebraska , Tennessee, Utah , Virginia; Non-attending stations in 2003 and 2004: Minnesota, Nebraska, Arkansas, Utah
The NCR204 project convened Saturday February 12, 2003 in Berkeley, California at Sygen research offices. Jeanne Romero-Severson introduced the new secretary, Jean-Luc Jannink and Anne-Marie Thro, the CSREES representative. The objectives of the project are: 1. Develop and compare statistical methodology to map genes; 2. Examine the efficiency of incorporation molecular tools in breeding programs through theoretical modeling, computer simulations, and biological testing in actual breeding populations; and 3. Use molecular genetics to test hypotheses generated from the fundamental theories of population, quantitative genetics, and molecular evolutionary genetics.
Bill Muir from Purdue, Shizhong Xu from UC Riverside, Ignacy Misztal from U. Georgia, and Jean-Luc Jannink Iowa State University gave research reports.
The business meeting was held 13 February. We discussed: 1. A more rapid mechanism to get the minutes out; 2. A common data set to analyze; 3. Policy surrounding non-attending stations; 4. A secretary is elected, serves as secretary one year and become chair the next year; 5 Elected Guilherme Rosa, Michigan State University, to be secretary in 2004-2005, David Henderson, U. Arizona to be objective coordinator for Objective 1, and Shizhong Xu, UC Riverside, to be ?Local Host? for NCR-204 at the Gordon Conference; 6 Margaret Dentine (Administrative Advisor) discussed CRIS codes in Appendix E of the NCR-204 document, a topic that was recurrent from the 2003 meeting; 7 Mid term review will proceed with an examination of meeting minutes and attendance. A website on the NIMSS can be constructed. Send website materials to Gretel Dentine; 8 Anne Marie Thro discussed the organization of the USDA and where the NCR committees fit, emphasized the importance to Government of the Current Research Information Service (CRIS) codes, and discussed obtaining special grants monies.
Rohan Fernando from Iowa State University, Guilherme Rosa from Michigan State University, John Bastiaansen from Sygen, Jeanne Romero-Severson from Notre Dame, and David Henderson from U. Arizona presented research reports.
Bill Muir from Purdue, Shizhong Xu from UC Riverside, Ignacy Misztal from U. Georgia, and Jean-Luc Jannink Iowa State University gave research reports.
The business meeting was held 13 February. We discussed: 1. A more rapid mechanism to get the minutes out; 2. A common data set to analyze; 3. Policy surrounding non-attending stations; 4. A secretary is elected, serves as secretary one year and become chair the next year; 5 Elected Guilherme Rosa, Michigan State University, to be secretary in 2004-2005, David Henderson, U. Arizona to be objective coordinator for Objective 1, and Shizhong Xu, UC Riverside, to be ?Local Host? for NCR-204 at the Gordon Conference; 6 Margaret Dentine (Administrative Advisor) discussed CRIS codes in Appendix E of the NCR-204 document, a topic that was recurrent from the 2003 meeting; 7 Mid term review will proceed with an examination of meeting minutes and attendance. A website on the NIMSS can be constructed. Send website materials to Gretel Dentine; 8 Anne Marie Thro discussed the organization of the USDA and where the NCR committees fit, emphasized the importance to Government of the Current Research Information Service (CRIS) codes, and discussed obtaining special grants monies.
Rohan Fernando from Iowa State University, Guilherme Rosa from Michigan State University, John Bastiaansen from Sygen, Jeanne Romero-Severson from Notre Dame, and David Henderson from U. Arizona presented research reports.
Accomplishments
Objective 1: Develop and compare statistical methodology to map genes
Xu (UC Riverside) has developed Bayesian QTL mapping methodology that allows for more independent variables in the model than there are observations. This methodology has a fixed-dimensional space and so does not use reversible jump approaches. Its advantages include that it is computationally simpler, converges more rapidly, has excellent estimation properties for the allelic effects, and has output that is simpler to interpret than reversible jump approaches. The approach worked even when >7200 epistatic effects were included in the model.
Misztal (U. Georgia) has developed QXPAK, which aims at simplifying QTL analysis and future genetical genomics data analyses implementing a coherent and unified mixed model approach. The goal is to provide a software that can be used in a wide variety of situations with ample genetic and statistical modeling flexibility. The program is modular and so has advantages for teaching.
Jannink (Iowa State U.) has assessed different priors in Bayesian analysis for QTL mapping in multiple families. With multiple families, all parents may carry different alleles or some parents may be identical in state for the QTL alleles (that is, they carry alleles that have equal effects on the phenotype). If you make that latter assumption, you do not have to estimate as many QTL effects, and that could be advantageous because it can reduce the entropy of the QTL effect prior. Using ?low entropy priors? did not increase QTL detection power.
Fernando (Iowa State U.) has explored fine mapping methods using LD with a series of tightly linked makers, as proposed by Meuwissen and Goddard (2000). Simple regression on single markers can map more accurately than the IBD given IIS approach, in part because simple regression has lower genotyping costs: you do not need to genotype the parents to get marker phase information. Fernando found that the Meuwissen and Goddard approach works optimally with a small number of markers: 4 worked better than 10. This finding is paradoxical because it means that more accurate results are obtained with less information. Fernando also reported on a mapping approach using two markers in which one of the haplotypes is assumed to have carried the mutation. The approach worked better than all others.
Rosa (Michigan State U.) reported on simulations of QTL analyses when genotyping errors are present. A 1% error rate can generate a bimodal posterior distribution for QTL position. Model allowing errors in genotyping can correct this problem. In a Bayesian framework, a prior distribution for the error rate is given. Rosa also discussed issues of the error term to use in microarray experiments: technical versus biological replication, the importance of identifying the treatment groups and having biological replication within them.
Romero-Severson (Notre Dame) discussed the experimental design of a microarray experiment to identify expression differences between refractory (cannot transmit) and competent (can transmit) mosquitoes with dengue fever infected blood versus non-infected blood including a time course: 1, 2, 6, 12, 24 hrs after blood meal.
David Henderson (U. Arizona) discussed the statistical analysis of microarray experiments. Controlling type I errors using Westfall and Young approach versus a Bonferroni approach: the latter is more stringent. Another option is to use Bayesian shrinkage estimators of the residual variances. He also discussed receiver operator curve (ROC), which has its roots in epidemiology and helps you decide what type 1 error you want to optimize the tradeoff between type 1 and type 2 errors. Finally, Henderson discussed stochastic search variable selection procedures for microarray data analysis.
Objective 2: Examine the efficiency of incorporating molecular tools in breeding programs through theoretical modeling, computer simulations, and biological testing in actual breeding populations.
Muir (Purdue), performed simulations assessing the efficiency of whole genome marker assisted selection. In this approach, each marker haplotype is considered a random effect that is predicted using a mixed-model BLUP approach. Muir assumed 50 possible haplotypes every 1 cM over a 1000 cM genome for a total of 50,000 random effects. Muir found that: 1. Using a population in linkage equilibrium is OK because the smaller populations used to predict haplotype effects generate LD; 2. Using markers with few alleles works as well are markers with many alleles; 3. The approach appears to overcome the Lande and Thompson heritability paradox in that it works for traits with low heritability; 4. After two generations of joint phenotype / marker haplotype data analysis, phenotyping can be skipped for a generation.
Bastiaansen (Sygen) gave an overview of Sygen efforts in applying genomics. He did not give specifics on approaches that are being used.
Objective 3: Use molecular genetics to test hypotheses generated from the fundamental theories of population, quantitative, molecular and evolutionary genetics.
No station reports included results relevant to this objective.
Xu (UC Riverside) has developed Bayesian QTL mapping methodology that allows for more independent variables in the model than there are observations. This methodology has a fixed-dimensional space and so does not use reversible jump approaches. Its advantages include that it is computationally simpler, converges more rapidly, has excellent estimation properties for the allelic effects, and has output that is simpler to interpret than reversible jump approaches. The approach worked even when >7200 epistatic effects were included in the model.
Misztal (U. Georgia) has developed QXPAK, which aims at simplifying QTL analysis and future genetical genomics data analyses implementing a coherent and unified mixed model approach. The goal is to provide a software that can be used in a wide variety of situations with ample genetic and statistical modeling flexibility. The program is modular and so has advantages for teaching.
Jannink (Iowa State U.) has assessed different priors in Bayesian analysis for QTL mapping in multiple families. With multiple families, all parents may carry different alleles or some parents may be identical in state for the QTL alleles (that is, they carry alleles that have equal effects on the phenotype). If you make that latter assumption, you do not have to estimate as many QTL effects, and that could be advantageous because it can reduce the entropy of the QTL effect prior. Using ?low entropy priors? did not increase QTL detection power.
Fernando (Iowa State U.) has explored fine mapping methods using LD with a series of tightly linked makers, as proposed by Meuwissen and Goddard (2000). Simple regression on single markers can map more accurately than the IBD given IIS approach, in part because simple regression has lower genotyping costs: you do not need to genotype the parents to get marker phase information. Fernando found that the Meuwissen and Goddard approach works optimally with a small number of markers: 4 worked better than 10. This finding is paradoxical because it means that more accurate results are obtained with less information. Fernando also reported on a mapping approach using two markers in which one of the haplotypes is assumed to have carried the mutation. The approach worked better than all others.
Rosa (Michigan State U.) reported on simulations of QTL analyses when genotyping errors are present. A 1% error rate can generate a bimodal posterior distribution for QTL position. Model allowing errors in genotyping can correct this problem. In a Bayesian framework, a prior distribution for the error rate is given. Rosa also discussed issues of the error term to use in microarray experiments: technical versus biological replication, the importance of identifying the treatment groups and having biological replication within them.
Romero-Severson (Notre Dame) discussed the experimental design of a microarray experiment to identify expression differences between refractory (cannot transmit) and competent (can transmit) mosquitoes with dengue fever infected blood versus non-infected blood including a time course: 1, 2, 6, 12, 24 hrs after blood meal.
David Henderson (U. Arizona) discussed the statistical analysis of microarray experiments. Controlling type I errors using Westfall and Young approach versus a Bonferroni approach: the latter is more stringent. Another option is to use Bayesian shrinkage estimators of the residual variances. He also discussed receiver operator curve (ROC), which has its roots in epidemiology and helps you decide what type 1 error you want to optimize the tradeoff between type 1 and type 2 errors. Finally, Henderson discussed stochastic search variable selection procedures for microarray data analysis.
Objective 2: Examine the efficiency of incorporating molecular tools in breeding programs through theoretical modeling, computer simulations, and biological testing in actual breeding populations.
Muir (Purdue), performed simulations assessing the efficiency of whole genome marker assisted selection. In this approach, each marker haplotype is considered a random effect that is predicted using a mixed-model BLUP approach. Muir assumed 50 possible haplotypes every 1 cM over a 1000 cM genome for a total of 50,000 random effects. Muir found that: 1. Using a population in linkage equilibrium is OK because the smaller populations used to predict haplotype effects generate LD; 2. Using markers with few alleles works as well are markers with many alleles; 3. The approach appears to overcome the Lande and Thompson heritability paradox in that it works for traits with low heritability; 4. After two generations of joint phenotype / marker haplotype data analysis, phenotyping can be skipped for a generation.
Bastiaansen (Sygen) gave an overview of Sygen efforts in applying genomics. He did not give specifics on approaches that are being used.
Objective 3: Use molecular genetics to test hypotheses generated from the fundamental theories of population, quantitative, molecular and evolutionary genetics.
No station reports included results relevant to this objective.
Impacts
- Several computer programs were developed to analyze marker data for detecting loci affecting quantitative traits including the effects of epistatic interactions.
- Several analytical methods were compared as well as the results of assumptions included in the models. Researchers can utilize these methods more confidently and report results and implications more accurately using these tools.
- Methods to design microchips for investigations and analytical strategies for interpreting microarray data were investigated and compared. These tools will enable more efficient and effective use of microarray data in investigations.
Publications
Georgia
Wiggans, G.R., I. Misztal, and C.P. Van Tassell. Calving ease (co)variance components for a sire-maternal grandsire threshold model. J. Dairy Sci. 86:1845?1848. 2003.
Van Tassell, C.P., G.R. Wiggans, and I. Misztal. Implementation of a sire-maternal grandsire model for evaluation of calving ease in the United States. J. Dairy Sci. 86:3366?3373. 2003.
Oseni, S., I. Misztal, S. Tsuruta, and R. Rekaya. Seasonality of days open in US Holsteins. J. Dairy Sci. 86: 3718?3725. 2003.
Nobre, P.R.C., I. Misztal, S. Tsuruta, J.K. Bertrand, L.O.C. Silva, and P.S. Lopes. Analyses of growth curves of Nellore cattle by multiple-trait and random regression models. J. Anim. Sci. 81:918?926. 2003.
Nobre, P.R.C., I. Misztal, S. Tsuruta, J.K. Bertrand, L.O.C. Silva, and P.S. Lopes. Genetic evaluation of growth in Nellore cattle by multiple-trait and random regression models. J. Anim. Sci. 81:927?932. 2003.
Pribyl, J., I. Misztal, J. Pribylová, and K. ?eba. Multiple-breed, multiple-traits evaluation of beef cattle in the Czech Republic. Czech J. Anim. Sci. 48:519?532. 2003.
Tsuruta, S., I. Misztal, T.J. Lawlor, and L. Klei. Estimation of genetic correlations among production, body size, udder, and productive life traits over time in Holsteins (abstract). J. Dairy Sci. 86(Suppl. 1)/J. Anim. Sci. 81(Suppl. 1):38. 2003.
Misztal, I., S. Oseni, and S. Tsuruta. Analyses of heat tolerance for milk in Holsteins using different sources of heat-stress information (abstract). J. Dairy Sci. 86(Suppl. 1)/J. Anim. Sci. 81(Suppl. 1):39. 2003.
Sapp, R.L., R. Rekaya, J.K. Bertrand, I. Misztal, and K.A. Donoghue. Genetic parameter estimates of udder scores in Gelbvieh cattle (abstract). J. Dairy Sci. 86(Suppl. 1)/J. Anim. Sci. 81(Suppl. 1):88. 2003.
Tsuruta, S., I. Misztal, and T. Druet. Comparison of estimation methods for heterogeneous residual variances with random regression models (abstract). J. Dairy Sci. 86(Suppl. 1)/J. Anim. Sci. 81(Suppl. 1):113. 2003.
Legarra, A., I. Misztal, and J. Jamrozik. Plotting covariance functions from random regression models (abstract). J. Dairy Sci. 86(Suppl. 1)/J. Anim. Sci. 81(Suppl. 1):114. 2003.
Oseni, S., and I. Misztal. Seasonality of days open in US Holsteins (abstract). J. Dairy Sci. 86(Suppl. 1)/J. Anim. Sci. 81(Suppl. 1):131. 2003.
Legarra, A., T. Strabel, J.K. Bertrand, and I. Misztal. Setting up the Gelbvieh multiple breed evaluation. J. Dairy Sci. 86(Suppl. 1)/J. Anim. Sci. 81(Suppl.):198. 2003.
Bohmanova, J., I. Misztal, and J. Pribyl. Differences in growth trajectories in seven beef breeds (abstract). J. Dairy Sci. 86(Suppl. 1)/J. Anim. Sci. 81(Suppl. 1):198. 2003.
Michigan State
Rosa, G. J. M. Accounting for genotyping errors in QTL analyses. J. Anim. Sci. 81 (Suppl. 1): 159-160, 2003.
De Leon, N., Coors, J. G., Kaeppler, S. M., Rosa, G. J. M. Genetic control of the number of ears per plant and related morphological traits in the Golden Glow maize population. Maize Genetics Conference Abstracts 45: P181, 2003.
Dreher, B. P., Rosa, G. J. M., Scribner, K. T., Winterstein, S. R., Lopez, V. A., Libants, S. V., Etter, D. R. How many bears, plus or minus: effects of errors associated with non-invasive population size estimation. Abstracts of the Wildlife Society National Meeting. Burlington, Vermont. September, 2003.
Coussens, P. M., Colvin, C. J., Rosa, G. J. M., Laspiur, J. P., Elftman, M. D. Evidence for a novel gene expression program in peripheral blood mononuclear cells from M. paratuberculosis-infected cattle. Infection and Immunity, 71(11): 6487-6498, 2003.
Madsen, S. A., Rosa, G. J. M., Mccandless, E., Coussens, P. M., Burton, J. L. Microarray analysis of gene expression in blood neutrophils of parturient cows. Physiological Genomics, 2003. (on line http://physiolgenomics.physiology.org/papbyrecent.shtml).
Rosa, G. J. M., Tempelman, R. J., Suchyta, S., Madsen, S. A., Burton, J. L., Coussens, P. M. Normalization, replication, and significance tests in cDNA microarray experiments. J. Dairy. Sci. 86 (Suppl. 1): 159, 2003.
Etchebarne, B. E. Silva, L. F. P., Rosa, G. J. M., Coussens, P. M., Weber Nielsen, M. S., Vandehaar, M. J. IGF-I infusion alters gene expression profile of prepuberal bovine mammary parenchyma. J. Dairy. Sci. 86 (Suppl. 1): 165, 2003.
Etchebarne, B. E. Silva, L. F. P., Rosa, G. J. M., Coussens, P. M., Weber Nielsen, M. S., Vandehaar, M. J. Leptin intramammary infusion alters gene expression profile of prepuberal bovine mammary parenchyma. J. Dairy. Sci. 86 (Suppl. 1): 166, 2003.
Chan, P. S., Schlueter, A. E., Coussens, P. M., Rosa, G. J. M., Haut, R. C., Orth, M. W. (2003) Gene Expression Profile of Mechanically Impacted Bovine Articular Cartilage Explants. Proc. International Symposium on Animal Functional Genomics, East Lansing, MI. May 9-11, 2003.
Madsen, S. A., Chang, L.-C., Hickey, M.-C., Coussens, P. M., Rosa, G. J. M., Burton, J. L. (2003) Gene expression profiling and apoptosis phenotyping indicate that parturient steroids promote survival in bovine blood neutrophils. Proc. International Symposium on Animal Functional Genomics, East Lansing, MI. May 9-11, 2003.
Steibel, J. P., Tempelman, R. J., Rosa, G. J. M. Thick-tailed and heteroskedastic linear models for the analysis of cDNA microarray data. Proc. International Symposium on Animal Functional Genomics, East Lansing, MI. May 9-11, 2003.
Hill, E. W., O?gorman, G. M., Gormley, E., Fitzpatrick, T., Rosa, G. J. M., Coussens, P. M., Machugh, D. E. Functional Genomics Analysis of the Bovine Immune Response of In Vitro Co-Culture with Trypanosomes (Trypanosoma brucei). Proc. International Symposium on Animal Functional Genomics, East Lansing, MI. May 9-11, 2003.
Meade, K., Gormley, E., Fitzpatrick, T., Rosa, G. J. M., Coussens, P. M., Machugh, D. E. Analysis of Host Gene Expression in Tuberculosis-Infected Cattle Using In Vitro Stimulation of Peripheral Blood Mononuclear Cells (PBMC) and cDNA Microarrays. Proc. International Symposium on Animal Functional Genomics, East Lansing, MI. May 9-11, 2003.
Etchebarne, B. E., Silva, L. F. P., Rosa, G. J. M., Coussens, P. M., Weber Nielsen, M., Vandehaar, M. J. How do the hormones leptin and IGF-I affect the nutritional regulation of mammary development? Proc. International Symposium on Animal Functional Genomics, East Lansing, MI. May 9-11, 2003.
Rosa, G. J. M., Gianola, D., Padovani, C. R. Robust linear mixed models with normal/independent distributions and Bayesian MCMC implementation. Biometrical Journal, 45(5): 573-590, 2003.
Rosa, G. J. M., Gianola, D., Padovani, C. R. Bayesian longitudinal data analysis with mixed models and thick-tailed distributions using MCMC. Journal of Applied Statistics. (accepted)
Purdue
Cheng, H.W., P. Singleton and W.M. Muir. 2003. Social stress differentially regulates neuroendocrine responses in laying hens: I. Genetic basis of dopamine responses under three different social conditions. Psychoneuroendocrinology 28:597-611.
Cheng, H.W., P. Singleton and W.M. Muir. 2003. Social stress in laying hens: Differential effect of stress on plasma dopamine concentrations and adrenal function in genetically selected chickens. Poult. Sci. 82:192-198.
Muir, W.M.. 2003. Incorporating Molecular Information in Breeding Programs, Applications and Limitations. Chapter 28 p549-562. In Poultry Breeding and Biotechnology Eds. WM Muir and S Aggrey. CABI Press Cambridge MA.
Muir, W.M.. 2003. Indirect Selection for Improvement of Animal Well-Being. Chapter 14, p247-256. In Poultry Breeding and Biotechnology Eds. WM Muir and S Aggrey. CABI Press Cambridge MA.
Muir, W.M., D. Miles, and A.E. Bell, 2003. Long Term Selection Studies In Tribolium Castaneum, Alternative Selection Strategies, And Associated Nature Of Quantitative Genetic Variation. Plant Breeding Reviews (In Press)
Hostetler, HA., SL Peck, and W.M. Muir. 2003 High efficiency production of germ-line transgenic Japanese medaka (Oryzias latipes) by electroporation with direct current-shifted radio frequency pulses. Transgene Research (in press)
Notre Dame
Rider S.D., J.T. Henderson, R.E. Jerome, H.J. Edenberg, J. Romero-Severson, J.P.Ogas. 2003 Coordinate repression of regulators of embryonic identity by pickle during germination in Arabidopsis. The Plant Journal 35 (1): 33-43
Lobo N.F, L.Q. Ton, C.A. Hill, C.Emore, J. Romero-Severson, G.J. Hunt, F.H. Collins. 2003. Genomic Analysis in the sting-2 Quantitative Trait Locus for Defensive Behavior in the Honey Bee, Apis mellifera. Genome Res. 13:2588-2593
Lu H., J. Romero-Severson , R. Bernardo 2003 Genetic basis of heterosis explored by simple sequence repeat markers in a random-mated maize population. Theor Appl Genet 107 (3): 494-502
Feder J.L. J. Roethele, K. Fichak, J. Niebdalski, J. Romero-Severson. 2003 Evidence for inversion polymorphism related to sympatric host race formation in the apple maggot fly, Rhagoletis pomonella. Genetics 163: 939-953
Aldrich P.R., G. R. Parker, C. H. Michler, J. Romero-Severson. 2003 Whole-tree silvic identifications and the microsatellite genetic structure of a red oak species complex in an Indiana old-growth forest. Can J Forest Res 33:2228-2237
Iowa
Chen, P., T.J. Baas, J.C.M. Dekkers, K.J. Koehler and J.W. Mabry J. 2003. Evaluation of strategies for selection for lean growth rate in pigs. J. Anim. Sci. 81:1150-1157
Chen, P., T.J. Baas, J.W. Mabry, K.J. Koehler, and J.C.M. Dekkers. 2003. Genetic parameters and trends for litter traits in U.S. Yorkshire, Duroc, Hampshire, and Landrace pigs. J. Animal Sci. 81:46-53
Ciobanu, D.C., J.W.M. Bastiaansen, S.M. Lonergan, H. Thomsen, J.C.M. Dekkers, G.S. Plastow, and M.F. Rothschild. 2004. New alleles in calpastatin gene are associated with meat quality traits in pigs. J. Animal Sci. (Accepted).
Dekkers, J.C.M. 2004. Commercial application of marker- and gene-assisted selection in livestock: strategies and lessons. J. Anim. Sci. (Accepted subject to minor revision)
Dekkers, J.C.M., and P. Settar. 2003. Long-term Selection with Known Quantitative Trait Loci. Plant Breeding Reviews. Wiley. Plant Breeding Reviews, Volume 24, Part 1, Long Term Selection: Maize. edited by Jules Janick. John Wiley&Sons, Inc. Pp: 311-336 (invited presentation).
Dekkers, J.C.M., and R. Chakraborty. 2004. Optimizing purebred selection for crossbred performance using QTL. Genet. Sel. Evol. (Accepted)
Dorman, K. S., Sinsheimer, J. S. and K. Lange (2004) In the Garden of Branching Processes. SIAM Review. Accepted for publication.
Fernando, R.L. and L.R. Totir. 2003. Incorporating Molecular Informationin Breeding Programs: Methodology. In ?Poultry Breeding andBiotechnology?. CABI Publishing, Cambridge.
Fernando, R.L., D. Nettleton, B.R. Southey, J.C.M. Dekkers, M.F. Rothschild, and M. Soller. 2004. Controlling the proportion of false positives (PFP) in multiple dependent tests. Genetics (In press)
Grapes, L., J.C.M. Dekkers, M.F. Rothschild, and R.L. Fernando. 2004. Comparing linkage disequilibrium-based methods for fine mapping quantitative trait loci. Genetics (Accepted).
Jannink, J.-L., and R.L. Fernando. 2003. On the Metropolis-Hastings acceptance probability to add or drop a QTL in MCMC-based Bayesian analyses. Genetics 165:In Press.
Jannink, J.-L., and X.-L. Wu. 2003. Estimating allelic number and identity in state of QTL in interconnected families. Genet Res 81:133-144.
Kulak, K., J. Wilton, G. Fox and J. Dekkers. 2003. Comparisons of economic values with and without risk for livestock trait improvement Livestock Production Science, 79: 183-191.
Lall, S., Nettleton, D., DeCook, R., Che, P., Howell, S. H. (2004). QTLs affecting adventitious shoot formation in tissue culture and the program of shoot development in Arabidopsis. Acceptance pending revisions from Genetics.
Thomsen, H., J.C.M. Dekkers, H. K. Lee, and M. F. Rothschild 2004. Characterization of quantitative trait loci for growth and meat quality in a cross between commercial breeds of swine J. Anim. Sci. (Accepted subject to minor revision)
Totir, L. R., R.L. Fernando, J.C.M. Dekkers, S.A. Fernandez, and B.Guldbrandtsen. 2003. A comparison of alternative methods to computeconditional genotype probabilities for genetic evaluation with finite locusmodels. Genet. Sol. Evol 35: 1-20.
Totir, L.R., R.L. Fernando, and J.C.M. Dekkers. 2003. Response to selectionby marker assisted BLUP with use of approximate gametic variancecovariance matrices. J. Anim. Sci. 81 (Suppl. 1)
Totir, L.R., R.L. Fernando, J.C.M. Dekkers, S.A. Fernandez, and B. Guldbrandtsen. 2004. Effect of using approximate gametic variance covariance matrices on marker assisted selection by BLUP. Genet. Sel. Evol. 36:29-48.
Totir, L.R., R.L. Fernando, J.C.M. Dekkers, S.A. Fernandez, and B Guldbrandtsen. 2003. A comparison of alternative methods to compute conditional genotype probabilities for genetic evaluation with finite locus models. Genet. Sel. Evol. 35:1-20
Villanueva, B., J.C.M. Dekkers, J.A. Woolliams and P. Settar. 2004. Maximising genetic gain over multiple generations with QTL information and control of inbreeding. Genet. Sel. Evol. (Accepted).
Wagter, L.C., B.A. Mallard, B.N. Wilkie, K.E. Leslie, P.J. Boettcher, and J.C.M. Dekkers. 2003. The Relationship Between Milk Production and Antibody Response to Ovalbumin During the Peripartum Period. J. Dairy Sci. 86: 169-173.
Wu, X.-L., and J.-L. Jannink. 2003. Optimal sampling of a population to determine QTL location, variance, and allelic number. Theor Appl Genet:Accepted.
Zhao, H., M. F. Rothschild, R.L. Fernando, and J.C.M. Dekkers. 2003. Tests of candidate genes in breed cross population for QTL mappping in livestock. Mammalian Genome 14: 472-482
UC Riverside
Yi, N., S. Xu and D. B. Allison. 2003. Bayeisan model choice and search strategies for mapping interacting quantitative trait loci. Genetics 165:867-883.
Yi, N., S. Xu, V. George and D. B. Allison. 2004. Mapping multiple quantitative trait loci for ordinal traits. Behavior Genetics 34:3-14.
Xu, S., N. Yi, D. Burke, A. Galecki, and R. A. Miller. 2003. An EM algorithm for mapping binary disease loci: application to fibrosarcoma in a four-way cross mouse family. Genetical Research 82:127-138.
Xu, S. 2003. Theoretical basis of the Beavis effect. Genetics 165:2259-2268.
Qu, Y. and S. Xu. 2004. Supervised cluster analysis for microarray data based on multivariate Gaussian mixture. Bioinformatics (in press)
Zhang, Y.?M. and S. Xu. 2004. Mapping quantitative trait loci in F2 incorporating phenotypes of F3 progeny. Genetics (in press)
Mao, Y. and S. Xu. 2004. Mapping QTL for traits measured as percentage. Genetical Research (in press)
Xu, S., C. Xu and Z. Li. 2004. Joint mapping of quantitative trait loci for multiple binary characters. Genetics (accepted, pending revision)
Wang, H., X. Li, G. L. Masinde, S. Mohan, D. J. Baylink, and S. Xu. 2004. Bayesian shrinkage estimation of QTL parameters. Genetics (submitted).
Mao, Y. and S. Xu. 2004. A Monte Carlo algorithm for computing the IBD matrices using incomplete marker information. Heredity (submitted)
Zhang, Y.-M., Y. Mao, C. Xie, H. Smith, L. Luo, and S. Xu. 2004. Mapping QTL using naturally occurring genetic variance among commercial inbred lines. Genetics (submitted).
Illinois
Bohn, M., T. Magg, D. Klein, and A.E. Melchinger. 2003. Breeding early maturing European Dent maize (Zea mays L.) for improved agronomic performance and resistance against the European corn borer (Ostrinia nubilalis Hb.). Maydica 48:239-247.
Magg, T., M. Bohn, D. Klein, and A.E. Melchinger. 2003. Concentration of moniliformin produced by Fusarium species in grains of transgenic Bt maize hybrids compared to their isogenic counterparts and commercial varieties under European corn borer (Ostrinia nubilalis Hb.) pressure. Plant Breeding 122:322-327.
Heckenberger, M., M. Bohn, J.R. van der Voort, J. Peleman, and A.E. Melchinger. 2003. Variation of DNA fingerprints among accessions within maize inbred lines and implications for identification of essentially derived varieties: II. Genetic and technical sources of variation in AFLP data and comparison with SSR data. Molecular Breeding. 12:97-106.
Reif, J.C., A.E. Melchinger, X.C. Xia, M. Warburton, D.A. Hoisington, S.K. Vasal, D. Beck, M. Bohn, and M. Frisch. 2003. Use of SSRs for establishing heterotic groups in subtropical maize. Theor. Appl. Genet. 107:947-957.
Reif, J. C., A. E. Melchinger, X. C. Xia, M. L. Warburton, D. A. Hoisington, S. K. Vasal, G. Srinivasan, M. Bohn, and M. Frisch. 2003. Genetic distance based on simple sequence repeats and heterosis in tropical maize. Crop Sci. 43: 1275-1282.
SOFTWARE RELEVANT TO NCR-204
QXPAK to jointly analyze QTL and polygenic traits in single-and multiple-trait models.
http://nce.ads.uga.edu/~ignacy/newprograms.html
Developed by Ignacy Misztal at U. Georgia
Wiggans, G.R., I. Misztal, and C.P. Van Tassell. Calving ease (co)variance components for a sire-maternal grandsire threshold model. J. Dairy Sci. 86:1845?1848. 2003.
Van Tassell, C.P., G.R. Wiggans, and I. Misztal. Implementation of a sire-maternal grandsire model for evaluation of calving ease in the United States. J. Dairy Sci. 86:3366?3373. 2003.
Oseni, S., I. Misztal, S. Tsuruta, and R. Rekaya. Seasonality of days open in US Holsteins. J. Dairy Sci. 86: 3718?3725. 2003.
Nobre, P.R.C., I. Misztal, S. Tsuruta, J.K. Bertrand, L.O.C. Silva, and P.S. Lopes. Analyses of growth curves of Nellore cattle by multiple-trait and random regression models. J. Anim. Sci. 81:918?926. 2003.
Nobre, P.R.C., I. Misztal, S. Tsuruta, J.K. Bertrand, L.O.C. Silva, and P.S. Lopes. Genetic evaluation of growth in Nellore cattle by multiple-trait and random regression models. J. Anim. Sci. 81:927?932. 2003.
Pribyl, J., I. Misztal, J. Pribylová, and K. ?eba. Multiple-breed, multiple-traits evaluation of beef cattle in the Czech Republic. Czech J. Anim. Sci. 48:519?532. 2003.
Tsuruta, S., I. Misztal, T.J. Lawlor, and L. Klei. Estimation of genetic correlations among production, body size, udder, and productive life traits over time in Holsteins (abstract). J. Dairy Sci. 86(Suppl. 1)/J. Anim. Sci. 81(Suppl. 1):38. 2003.
Misztal, I., S. Oseni, and S. Tsuruta. Analyses of heat tolerance for milk in Holsteins using different sources of heat-stress information (abstract). J. Dairy Sci. 86(Suppl. 1)/J. Anim. Sci. 81(Suppl. 1):39. 2003.
Sapp, R.L., R. Rekaya, J.K. Bertrand, I. Misztal, and K.A. Donoghue. Genetic parameter estimates of udder scores in Gelbvieh cattle (abstract). J. Dairy Sci. 86(Suppl. 1)/J. Anim. Sci. 81(Suppl. 1):88. 2003.
Tsuruta, S., I. Misztal, and T. Druet. Comparison of estimation methods for heterogeneous residual variances with random regression models (abstract). J. Dairy Sci. 86(Suppl. 1)/J. Anim. Sci. 81(Suppl. 1):113. 2003.
Legarra, A., I. Misztal, and J. Jamrozik. Plotting covariance functions from random regression models (abstract). J. Dairy Sci. 86(Suppl. 1)/J. Anim. Sci. 81(Suppl. 1):114. 2003.
Oseni, S., and I. Misztal. Seasonality of days open in US Holsteins (abstract). J. Dairy Sci. 86(Suppl. 1)/J. Anim. Sci. 81(Suppl. 1):131. 2003.
Legarra, A., T. Strabel, J.K. Bertrand, and I. Misztal. Setting up the Gelbvieh multiple breed evaluation. J. Dairy Sci. 86(Suppl. 1)/J. Anim. Sci. 81(Suppl.):198. 2003.
Bohmanova, J., I. Misztal, and J. Pribyl. Differences in growth trajectories in seven beef breeds (abstract). J. Dairy Sci. 86(Suppl. 1)/J. Anim. Sci. 81(Suppl. 1):198. 2003.
Michigan State
Rosa, G. J. M. Accounting for genotyping errors in QTL analyses. J. Anim. Sci. 81 (Suppl. 1): 159-160, 2003.
De Leon, N., Coors, J. G., Kaeppler, S. M., Rosa, G. J. M. Genetic control of the number of ears per plant and related morphological traits in the Golden Glow maize population. Maize Genetics Conference Abstracts 45: P181, 2003.
Dreher, B. P., Rosa, G. J. M., Scribner, K. T., Winterstein, S. R., Lopez, V. A., Libants, S. V., Etter, D. R. How many bears, plus or minus: effects of errors associated with non-invasive population size estimation. Abstracts of the Wildlife Society National Meeting. Burlington, Vermont. September, 2003.
Coussens, P. M., Colvin, C. J., Rosa, G. J. M., Laspiur, J. P., Elftman, M. D. Evidence for a novel gene expression program in peripheral blood mononuclear cells from M. paratuberculosis-infected cattle. Infection and Immunity, 71(11): 6487-6498, 2003.
Madsen, S. A., Rosa, G. J. M., Mccandless, E., Coussens, P. M., Burton, J. L. Microarray analysis of gene expression in blood neutrophils of parturient cows. Physiological Genomics, 2003. (on line http://physiolgenomics.physiology.org/papbyrecent.shtml).
Rosa, G. J. M., Tempelman, R. J., Suchyta, S., Madsen, S. A., Burton, J. L., Coussens, P. M. Normalization, replication, and significance tests in cDNA microarray experiments. J. Dairy. Sci. 86 (Suppl. 1): 159, 2003.
Etchebarne, B. E. Silva, L. F. P., Rosa, G. J. M., Coussens, P. M., Weber Nielsen, M. S., Vandehaar, M. J. IGF-I infusion alters gene expression profile of prepuberal bovine mammary parenchyma. J. Dairy. Sci. 86 (Suppl. 1): 165, 2003.
Etchebarne, B. E. Silva, L. F. P., Rosa, G. J. M., Coussens, P. M., Weber Nielsen, M. S., Vandehaar, M. J. Leptin intramammary infusion alters gene expression profile of prepuberal bovine mammary parenchyma. J. Dairy. Sci. 86 (Suppl. 1): 166, 2003.
Chan, P. S., Schlueter, A. E., Coussens, P. M., Rosa, G. J. M., Haut, R. C., Orth, M. W. (2003) Gene Expression Profile of Mechanically Impacted Bovine Articular Cartilage Explants. Proc. International Symposium on Animal Functional Genomics, East Lansing, MI. May 9-11, 2003.
Madsen, S. A., Chang, L.-C., Hickey, M.-C., Coussens, P. M., Rosa, G. J. M., Burton, J. L. (2003) Gene expression profiling and apoptosis phenotyping indicate that parturient steroids promote survival in bovine blood neutrophils. Proc. International Symposium on Animal Functional Genomics, East Lansing, MI. May 9-11, 2003.
Steibel, J. P., Tempelman, R. J., Rosa, G. J. M. Thick-tailed and heteroskedastic linear models for the analysis of cDNA microarray data. Proc. International Symposium on Animal Functional Genomics, East Lansing, MI. May 9-11, 2003.
Hill, E. W., O?gorman, G. M., Gormley, E., Fitzpatrick, T., Rosa, G. J. M., Coussens, P. M., Machugh, D. E. Functional Genomics Analysis of the Bovine Immune Response of In Vitro Co-Culture with Trypanosomes (Trypanosoma brucei). Proc. International Symposium on Animal Functional Genomics, East Lansing, MI. May 9-11, 2003.
Meade, K., Gormley, E., Fitzpatrick, T., Rosa, G. J. M., Coussens, P. M., Machugh, D. E. Analysis of Host Gene Expression in Tuberculosis-Infected Cattle Using In Vitro Stimulation of Peripheral Blood Mononuclear Cells (PBMC) and cDNA Microarrays. Proc. International Symposium on Animal Functional Genomics, East Lansing, MI. May 9-11, 2003.
Etchebarne, B. E., Silva, L. F. P., Rosa, G. J. M., Coussens, P. M., Weber Nielsen, M., Vandehaar, M. J. How do the hormones leptin and IGF-I affect the nutritional regulation of mammary development? Proc. International Symposium on Animal Functional Genomics, East Lansing, MI. May 9-11, 2003.
Rosa, G. J. M., Gianola, D., Padovani, C. R. Robust linear mixed models with normal/independent distributions and Bayesian MCMC implementation. Biometrical Journal, 45(5): 573-590, 2003.
Rosa, G. J. M., Gianola, D., Padovani, C. R. Bayesian longitudinal data analysis with mixed models and thick-tailed distributions using MCMC. Journal of Applied Statistics. (accepted)
Purdue
Cheng, H.W., P. Singleton and W.M. Muir. 2003. Social stress differentially regulates neuroendocrine responses in laying hens: I. Genetic basis of dopamine responses under three different social conditions. Psychoneuroendocrinology 28:597-611.
Cheng, H.W., P. Singleton and W.M. Muir. 2003. Social stress in laying hens: Differential effect of stress on plasma dopamine concentrations and adrenal function in genetically selected chickens. Poult. Sci. 82:192-198.
Muir, W.M.. 2003. Incorporating Molecular Information in Breeding Programs, Applications and Limitations. Chapter 28 p549-562. In Poultry Breeding and Biotechnology Eds. WM Muir and S Aggrey. CABI Press Cambridge MA.
Muir, W.M.. 2003. Indirect Selection for Improvement of Animal Well-Being. Chapter 14, p247-256. In Poultry Breeding and Biotechnology Eds. WM Muir and S Aggrey. CABI Press Cambridge MA.
Muir, W.M., D. Miles, and A.E. Bell, 2003. Long Term Selection Studies In Tribolium Castaneum, Alternative Selection Strategies, And Associated Nature Of Quantitative Genetic Variation. Plant Breeding Reviews (In Press)
Hostetler, HA., SL Peck, and W.M. Muir. 2003 High efficiency production of germ-line transgenic Japanese medaka (Oryzias latipes) by electroporation with direct current-shifted radio frequency pulses. Transgene Research (in press)
Notre Dame
Rider S.D., J.T. Henderson, R.E. Jerome, H.J. Edenberg, J. Romero-Severson, J.P.Ogas. 2003 Coordinate repression of regulators of embryonic identity by pickle during germination in Arabidopsis. The Plant Journal 35 (1): 33-43
Lobo N.F, L.Q. Ton, C.A. Hill, C.Emore, J. Romero-Severson, G.J. Hunt, F.H. Collins. 2003. Genomic Analysis in the sting-2 Quantitative Trait Locus for Defensive Behavior in the Honey Bee, Apis mellifera. Genome Res. 13:2588-2593
Lu H., J. Romero-Severson , R. Bernardo 2003 Genetic basis of heterosis explored by simple sequence repeat markers in a random-mated maize population. Theor Appl Genet 107 (3): 494-502
Feder J.L. J. Roethele, K. Fichak, J. Niebdalski, J. Romero-Severson. 2003 Evidence for inversion polymorphism related to sympatric host race formation in the apple maggot fly, Rhagoletis pomonella. Genetics 163: 939-953
Aldrich P.R., G. R. Parker, C. H. Michler, J. Romero-Severson. 2003 Whole-tree silvic identifications and the microsatellite genetic structure of a red oak species complex in an Indiana old-growth forest. Can J Forest Res 33:2228-2237
Iowa
Chen, P., T.J. Baas, J.C.M. Dekkers, K.J. Koehler and J.W. Mabry J. 2003. Evaluation of strategies for selection for lean growth rate in pigs. J. Anim. Sci. 81:1150-1157
Chen, P., T.J. Baas, J.W. Mabry, K.J. Koehler, and J.C.M. Dekkers. 2003. Genetic parameters and trends for litter traits in U.S. Yorkshire, Duroc, Hampshire, and Landrace pigs. J. Animal Sci. 81:46-53
Ciobanu, D.C., J.W.M. Bastiaansen, S.M. Lonergan, H. Thomsen, J.C.M. Dekkers, G.S. Plastow, and M.F. Rothschild. 2004. New alleles in calpastatin gene are associated with meat quality traits in pigs. J. Animal Sci. (Accepted).
Dekkers, J.C.M. 2004. Commercial application of marker- and gene-assisted selection in livestock: strategies and lessons. J. Anim. Sci. (Accepted subject to minor revision)
Dekkers, J.C.M., and P. Settar. 2003. Long-term Selection with Known Quantitative Trait Loci. Plant Breeding Reviews. Wiley. Plant Breeding Reviews, Volume 24, Part 1, Long Term Selection: Maize. edited by Jules Janick. John Wiley&Sons, Inc. Pp: 311-336 (invited presentation).
Dekkers, J.C.M., and R. Chakraborty. 2004. Optimizing purebred selection for crossbred performance using QTL. Genet. Sel. Evol. (Accepted)
Dorman, K. S., Sinsheimer, J. S. and K. Lange (2004) In the Garden of Branching Processes. SIAM Review. Accepted for publication.
Fernando, R.L. and L.R. Totir. 2003. Incorporating Molecular Informationin Breeding Programs: Methodology. In ?Poultry Breeding andBiotechnology?. CABI Publishing, Cambridge.
Fernando, R.L., D. Nettleton, B.R. Southey, J.C.M. Dekkers, M.F. Rothschild, and M. Soller. 2004. Controlling the proportion of false positives (PFP) in multiple dependent tests. Genetics (In press)
Grapes, L., J.C.M. Dekkers, M.F. Rothschild, and R.L. Fernando. 2004. Comparing linkage disequilibrium-based methods for fine mapping quantitative trait loci. Genetics (Accepted).
Jannink, J.-L., and R.L. Fernando. 2003. On the Metropolis-Hastings acceptance probability to add or drop a QTL in MCMC-based Bayesian analyses. Genetics 165:In Press.
Jannink, J.-L., and X.-L. Wu. 2003. Estimating allelic number and identity in state of QTL in interconnected families. Genet Res 81:133-144.
Kulak, K., J. Wilton, G. Fox and J. Dekkers. 2003. Comparisons of economic values with and without risk for livestock trait improvement Livestock Production Science, 79: 183-191.
Lall, S., Nettleton, D., DeCook, R., Che, P., Howell, S. H. (2004). QTLs affecting adventitious shoot formation in tissue culture and the program of shoot development in Arabidopsis. Acceptance pending revisions from Genetics.
Thomsen, H., J.C.M. Dekkers, H. K. Lee, and M. F. Rothschild 2004. Characterization of quantitative trait loci for growth and meat quality in a cross between commercial breeds of swine J. Anim. Sci. (Accepted subject to minor revision)
Totir, L. R., R.L. Fernando, J.C.M. Dekkers, S.A. Fernandez, and B.Guldbrandtsen. 2003. A comparison of alternative methods to computeconditional genotype probabilities for genetic evaluation with finite locusmodels. Genet. Sol. Evol 35: 1-20.
Totir, L.R., R.L. Fernando, and J.C.M. Dekkers. 2003. Response to selectionby marker assisted BLUP with use of approximate gametic variancecovariance matrices. J. Anim. Sci. 81 (Suppl. 1)
Totir, L.R., R.L. Fernando, J.C.M. Dekkers, S.A. Fernandez, and B. Guldbrandtsen. 2004. Effect of using approximate gametic variance covariance matrices on marker assisted selection by BLUP. Genet. Sel. Evol. 36:29-48.
Totir, L.R., R.L. Fernando, J.C.M. Dekkers, S.A. Fernandez, and B Guldbrandtsen. 2003. A comparison of alternative methods to compute conditional genotype probabilities for genetic evaluation with finite locus models. Genet. Sel. Evol. 35:1-20
Villanueva, B., J.C.M. Dekkers, J.A. Woolliams and P. Settar. 2004. Maximising genetic gain over multiple generations with QTL information and control of inbreeding. Genet. Sel. Evol. (Accepted).
Wagter, L.C., B.A. Mallard, B.N. Wilkie, K.E. Leslie, P.J. Boettcher, and J.C.M. Dekkers. 2003. The Relationship Between Milk Production and Antibody Response to Ovalbumin During the Peripartum Period. J. Dairy Sci. 86: 169-173.
Wu, X.-L., and J.-L. Jannink. 2003. Optimal sampling of a population to determine QTL location, variance, and allelic number. Theor Appl Genet:Accepted.
Zhao, H., M. F. Rothschild, R.L. Fernando, and J.C.M. Dekkers. 2003. Tests of candidate genes in breed cross population for QTL mappping in livestock. Mammalian Genome 14: 472-482
UC Riverside
Yi, N., S. Xu and D. B. Allison. 2003. Bayeisan model choice and search strategies for mapping interacting quantitative trait loci. Genetics 165:867-883.
Yi, N., S. Xu, V. George and D. B. Allison. 2004. Mapping multiple quantitative trait loci for ordinal traits. Behavior Genetics 34:3-14.
Xu, S., N. Yi, D. Burke, A. Galecki, and R. A. Miller. 2003. An EM algorithm for mapping binary disease loci: application to fibrosarcoma in a four-way cross mouse family. Genetical Research 82:127-138.
Xu, S. 2003. Theoretical basis of the Beavis effect. Genetics 165:2259-2268.
Qu, Y. and S. Xu. 2004. Supervised cluster analysis for microarray data based on multivariate Gaussian mixture. Bioinformatics (in press)
Zhang, Y.?M. and S. Xu. 2004. Mapping quantitative trait loci in F2 incorporating phenotypes of F3 progeny. Genetics (in press)
Mao, Y. and S. Xu. 2004. Mapping QTL for traits measured as percentage. Genetical Research (in press)
Xu, S., C. Xu and Z. Li. 2004. Joint mapping of quantitative trait loci for multiple binary characters. Genetics (accepted, pending revision)
Wang, H., X. Li, G. L. Masinde, S. Mohan, D. J. Baylink, and S. Xu. 2004. Bayesian shrinkage estimation of QTL parameters. Genetics (submitted).
Mao, Y. and S. Xu. 2004. A Monte Carlo algorithm for computing the IBD matrices using incomplete marker information. Heredity (submitted)
Zhang, Y.-M., Y. Mao, C. Xie, H. Smith, L. Luo, and S. Xu. 2004. Mapping QTL using naturally occurring genetic variance among commercial inbred lines. Genetics (submitted).
Illinois
Bohn, M., T. Magg, D. Klein, and A.E. Melchinger. 2003. Breeding early maturing European Dent maize (Zea mays L.) for improved agronomic performance and resistance against the European corn borer (Ostrinia nubilalis Hb.). Maydica 48:239-247.
Magg, T., M. Bohn, D. Klein, and A.E. Melchinger. 2003. Concentration of moniliformin produced by Fusarium species in grains of transgenic Bt maize hybrids compared to their isogenic counterparts and commercial varieties under European corn borer (Ostrinia nubilalis Hb.) pressure. Plant Breeding 122:322-327.
Heckenberger, M., M. Bohn, J.R. van der Voort, J. Peleman, and A.E. Melchinger. 2003. Variation of DNA fingerprints among accessions within maize inbred lines and implications for identification of essentially derived varieties: II. Genetic and technical sources of variation in AFLP data and comparison with SSR data. Molecular Breeding. 12:97-106.
Reif, J.C., A.E. Melchinger, X.C. Xia, M. Warburton, D.A. Hoisington, S.K. Vasal, D. Beck, M. Bohn, and M. Frisch. 2003. Use of SSRs for establishing heterotic groups in subtropical maize. Theor. Appl. Genet. 107:947-957.
Reif, J. C., A. E. Melchinger, X. C. Xia, M. L. Warburton, D. A. Hoisington, S. K. Vasal, G. Srinivasan, M. Bohn, and M. Frisch. 2003. Genetic distance based on simple sequence repeats and heterosis in tropical maize. Crop Sci. 43: 1275-1282.
SOFTWARE RELEVANT TO NCR-204
QXPAK to jointly analyze QTL and polygenic traits in single-and multiple-trait models.
http://nce.ads.uga.edu/~ignacy/newprograms.html
Developed by Ignacy Misztal at U. Georgia