Jean Luc Jannink

Summary

Affiliation: Agricultural Research Service
Country: USA

Publications

  1. ncbi On the Metropolis-Hastings acceptance probability to add or drop a quantitative trait locus in Markov chain Monte Carlo-based Bayesian analyses
    Jean Luc Jannink
    Department of Agronomy, Iowa State University, Ames, Iowa 50010 1010, USA
    Genetics 166:641-3. 2004
  2. ncbi Estimating allelic number and identity in state of QTLs in interconnected families
    Jean Luc Jannink
    Department of Agronomy, Iowa State University, Ames, IA 50011 1010, USA
    Genet Res 81:133-44. 2003
  3. ncbi Optimal sampling of a population to determine QTL location, variance, and allelic number
    Xiao-Lin Wu
    Department of Agronomy, Iowa State University, Ames, IA 50011-1010, USA
    Theor Appl Genet 108:1434-42. 2004
  4. ncbi Identifying quantitative trait locus by genetic background interactions in association studies
    Jean Luc Jannink
    Department of Agronomy, Iowa State University, Ames, Iowa 50011 1010, USA
    Genetics 176:553-61. 2007
  5. ncbi Using quantitative trait loci results to discriminate among crosses on the basis of their progeny mean and variance
    Shengqiang Zhong
    Department of Agronomy, Iowa State University, Ames, Iowa 50011 1010, USA
    Genetics 177:567-76. 2007
  6. ncbi New DArT markers for oat provide enhanced map coverage and global germplasm characterization
    Nicholas A Tinker
    Agriculture and Agri Food Canada, ECORC, K, W, Neatby Bldg, 960 Carling Ave, C, E, Farm, Ottawa, ON K1A 0C6, Canada
    BMC Genomics 10:39. 2009
  7. ncbi Population genetics of genomics-based crop improvement methods
    Martha T Hamblin
    Institute for Genomic Diversity, Biotechnology Building, Cornell University, Ithaca, NY 14853, USA
    Trends Genet 27:98-106. 2011
  8. ncbi Dynamics of long-term genomic selection
    Jean Luc Jannink
    USDA ARS, RW Holley Center for Agriculture and Health, Ithaca, NY 14853, USA
    Genet Sel Evol 42:35. 2010
  9. ncbi Genomic selection in plant breeding: from theory to practice
    Jean Luc Jannink
    USDA ARS, R W Holley Center for Agriculture and Health, Department of Plant Breeding and Genetics, Cornell University, Ithaca, New York 14853, USA
    Brief Funct Genomics 9:166-77. 2010
  10. ncbi Overview of QTL detection in plants and tests for synergistic epistatic interactions
    Jean Luc Jannink
    Robert W Holley Center for Agriculture and Health, USDA ARS, Ithaca, NY 14853 2901, USA
    Genetica 136:225-36. 2009

Collaborators

  • Jack C M Dekkers
  • Edward S Buckler
  • Hiroyoshi Iwata
  • Xiao Lin Wu
  • Shengqiang Zhong
  • Martha T Hamblin
  • Aaron J Lorenz
  • Nicholas A Tinker
  • Ni Yao
  • Pamela J White
  • Sedat Sayar
  • Marty L Carson
  • Eric W Jackson
  • Stine Tuvesson
  • Rohan L Fernando
  • Joseph M Anderson
  • Alf Ceplitis
  • Catherine J Howarth
  • Andrzej Kilian
  • Howard W Rines
  • Peter E Eckstein
  • Brian G Rossnagel
  • J Michael Bonman
  • Frederic L Kolb
  • Charlene P Wight
  • Mark E Sorrells
  • Graham J Scoles
  • Tim Langdon
  • Peter Wenzl
  • Herbert W Ohm
  • Katarzyna Heller-Uszynska
  • Luiz Carlos Federizzi
  • Olof Olsson
  • Deon D Stuthman
  • Asmund Bjørnstad
  • Stephen J Molnar
  • Sajid Alavi

Detail Information

Publications14

  1. ncbi On the Metropolis-Hastings acceptance probability to add or drop a quantitative trait locus in Markov chain Monte Carlo-based Bayesian analyses
    Jean Luc Jannink
    Department of Agronomy, Iowa State University, Ames, Iowa 50010 1010, USA
    Genetics 166:641-3. 2004
    ..Here, we show how accounting for this fact affects the acceptance probability and review expressions found in the literature...
  2. ncbi Estimating allelic number and identity in state of QTLs in interconnected families
    Jean Luc Jannink
    Department of Agronomy, Iowa State University, Ames, IA 50011 1010, USA
    Genet Res 81:133-44. 2003
    ..The variable analysis showed that, unless each family contains many individuals (more than 100), there is insufficient information in DNA-marker and phenotypic data to determine with high probability the QTL allelic number...
  3. ncbi Optimal sampling of a population to determine QTL location, variance, and allelic number
    Xiao-Lin Wu
    Department of Agronomy, Iowa State University, Ames, IA 50011-1010, USA
    Theor Appl Genet 108:1434-42. 2004
    ..Finally, strategies with an intermediate number of families best estimated the number of QTL alleles. We conclude that no overall optimal sampling strategy exists but that the strategy adopted must depend on the objective...
  4. ncbi Identifying quantitative trait locus by genetic background interactions in association studies
    Jean Luc Jannink
    Department of Agronomy, Iowa State University, Ames, Iowa 50011 1010, USA
    Genetics 176:553-61. 2007
    ..2, and then plateaued at about 80% as alleles reached intermediate frequencies. The power to detect epistasis declined when the linkage disequilibrium between the DNA marker and the functional polymorphism was not complete...
  5. ncbi Using quantitative trait loci results to discriminate among crosses on the basis of their progeny mean and variance
    Shengqiang Zhong
    Department of Agronomy, Iowa State University, Ames, Iowa 50011 1010, USA
    Genetics 177:567-76. 2007
    ....
  6. ncbi New DArT markers for oat provide enhanced map coverage and global germplasm characterization
    Nicholas A Tinker
    Agriculture and Agri Food Canada, ECORC, K, W, Neatby Bldg, 960 Carling Ave, C, E, Farm, Ottawa, ON K1A 0C6, Canada
    BMC Genomics 10:39. 2009
    ..This study was intended to develop, characterize, and apply a large set of oat genetic markers based on Diversity Array Technology (DArT)...
  7. ncbi Population genetics of genomics-based crop improvement methods
    Martha T Hamblin
    Institute for Genomic Diversity, Biotechnology Building, Cornell University, Ithaca, NY 14853, USA
    Trends Genet 27:98-106. 2011
    ....
  8. ncbi Dynamics of long-term genomic selection
    Jean Luc Jannink
    USDA ARS, RW Holley Center for Agriculture and Health, Ithaca, NY 14853, USA
    Genet Sel Evol 42:35. 2010
    ..Beyond those cycles, allele frequency changes, recombination, and inbreeding make analytical prediction of gain impossible. The impacts of GS on long-term gain should be studied prior to its implementation...
  9. ncbi Genomic selection in plant breeding: from theory to practice
    Jean Luc Jannink
    USDA ARS, R W Holley Center for Agriculture and Health, Department of Plant Breeding and Genetics, Cornell University, Ithaca, New York 14853, USA
    Brief Funct Genomics 9:166-77. 2010
    ..We then look forward and consider research needs surrounding methodological questions and the implications of GS for long-term selection...
  10. ncbi Overview of QTL detection in plants and tests for synergistic epistatic interactions
    Jean Luc Jannink
    Robert W Holley Center for Agriculture and Health, USDA ARS, Ithaca, NY 14853 2901, USA
    Genetica 136:225-36. 2009
    ..We fail to detect synergistic epistasis with the second method. We discuss our results in the light of theoretical questions concerning the mechanisms of synergistic epistasis...
  11. ncbi Performance of single nucleotide polymorphisms versus haplotypes for genome-wide association analysis in barley
    Aaron J Lorenz
    United States Department of Agriculture Agricultural Research Service, R W Holley Center for Agriculture and Health, Cornell University, Ithaca, New York, USA
    PLoS ONE 5:e14079. 2010
    ..We recommend routine use of both single SNP and haplotype markers for GWAS to take advantage of the full information content of the genotype data...
  12. ncbi Factors affecting accuracy from genomic selection in populations derived from multiple inbred lines: a Barley case study
    Shengqiang Zhong
    Department of Agronomy, Iowa State University, Ames, Iowa 50011, USA
    Genetics 182:355-64. 2009
    ....
  13. ncbi Digestion residues of typical and high-beta-glucan oat flours provide substrates for in vitro fermentation
    Sedat Sayar
    Department of Food Science and Human Nutrition and Department of Agronomy, Iowa State University, Ames, Iowa 50011, USA
    J Agric Food Chem 55:5306-11. 2007
    ..Glucose was the most rapidly consumed carbohydrate among other available monosaccharides in the fermentation medium. Overall, the high-beta-glucan experimental lines provided the best conditions for optimal in vitro gut fermentations...
  14. ncbi Impact of dry solids and bile acid concentrations on bile acid binding capacity of extruded oat cereals
    Ni Yao
    Department of Food Science and Human Nutrition, Iowa State University, Ames, Iowa 50011, USA
    J Agric Food Chem 56:8672-9. 2008
    ..Thus, greater BA binding capacity may have been caused by both a greater amount of beta-glucan and a greater solubility of beta-glucan in N979 than in Jim EBC...