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United States Department of Agriculture

Agricultural Research Service

Related Topics

Jean-Luc Jannink
Plant, Soil and Nutrition Research
Genetics

Phone: (607) 255-5266
Fax: (607) 255-6683

USDA,REE,ARS,NAA
ROBERT W. HOLLEY CENTER, TOWER ROAD
ITHACA , NY 148532901

Projects
RNAseq to Accelerate Oat Breeding for Nutritional Quality
General Cooperative Agreement (A)
  Accession Number: 429820
Develop Statistical Genetic Analyses for High-Dimensional Data
General Cooperative Agreement (A)
  Accession Number: 430195
Enhancing Breeding of Small Grains through Improved Bioinformatics
Appropriated (D)
  Accession Number: 424887
IMPROVING BARLEY AND WHEAT GERMPLASM FOR CHANGING ENVIRONMENTS
Reimbursable (R)
  Accession Number: 421067
Research and Training in High Throughput Genomics and Phenomics in Support of Bioinformatic Methods to Predict Small Grain Field Performance
Specific Cooperative Agreement (S)
  Accession Number: 428984
Providing Access to Oat Genomics Data and Improving Oat Breeding Data Management
Trust (T)
  Accession Number: 428118

Publications (Clicking on the reprint icon Reprint Icon will take you to the publication reprint.)
Population genetics related to adaptation in elite oat germplasm -
Esvelt Klos, K.L., Huang, Y., Babiker, E.M., Beattie, A., Bekele, W.A., Bjornstad, A., Bonman, J.M., Carson, M.L., Chao, S., Gnanesh, B.N., Harrison, S.A., Howarth, C.J., Hu, G., Ibrahim, A., Islamovic, E., Jackson, E.W., Jannink, J., Kolb, F.L., Mcmullen, M.S., Fetch, J.M., Murphy, J., Obert, D.E., Ohm, H.W., Rines, H.W., Rossnagel, B., Schuleter, J.A., Wight, C.P., Yan, W., Tinker, N.A. 2016. Population genetics related to adaptation in elite oat germplasm. The Plant Genome. doi: 10.3835/plantgenome2015.10.0103.
Genome-wide association and prediction analysis in African cassava (Manihot esculenta) reveals the genetic architecture of resistance to cassava mosaic disease and prospects for rapid genetic improvement -
Wolfe, M.D., Rabbi, I.Y., Egesi, C., Hamblin, M., Kawuki, R., Kulakow, P., Lozano, R., Del Carpio, D., Rumu, P., Jannink, J. 2016. Genome-wide association and prediction analysis in African cassava (Manihot esculenta) reveals the genetic architecture of resistance to cassava mosaic disease and prospects for rapid genetic improvement. Virus Research. 9. doi: 10.3835/plantgenome2015.11.0118.
An alternative covariance estimator to investigate genetic heterogeneity in populations -
Heslot, N., Jannink, J. 2015. An alternative covariance estimator to investigate genetic heterogeneity in populations. Genetics Selection Evolution. 47:93 doi: 10.1186/s12711-0150171-Z.
Genomic prediction using phenotypes from pedigreed lines with no marker data -
Ashraf, B., Edriss, V., Akdemir, D., Autrique, E., Bonnett, D., Crossa, J., Janss, L., Singh, R., Jannink, J. 2016. Genomic prediction using phenotypes from pedigreed lines with no marker data. Crop Science. 56(3):957-964.
The triticeae toolbox: combining phenotype and genotype data to advance small-grains breeding -
Blake, V., Birkett, C.L., Matthews, D.E., Hane, D., Bradbury, P., Jannink, J. 2015. The triticeae toolbox: combining phenotype and genotype data to advance small-grains breeding. The Plant Genome. doi: 10.3835/PlantGenome2014.12.0099.
Identification and distribution of the NBS-LRR gene family in the cassava genome -
Lozano, R., Hamblin, M., Prochnik, S., Jannink, J. 2015. Identification and distribution of the NBS-LRR gene family in the cassava genome. BMC Genomics. 16:360. doi: 10.1186/s12864-015-1554-9.
Optimization of genomic selection training populations with a genetic algorithm Reprint Icon -
Akdemir, D., Sanchez, J., Jannink, J. 2015. Optimization of genomic selection training populations with a genetic algorithm. Genetics Selection Evolution. 47:38.
Increased prediction accuracy in wheat breeding trials using a marker x environment interaction genomic selection model Reprint Icon -
Cruz, M., Crossa, J., Bonnett, D., Dreisigacker, S., Poland, J.A., Jannink, J., Singh, R., De Los Campos, G. 2015. Increased prediction accuracy in wheat breeding trials using a marker x environment interaction genomic selection model. Genes, Genomes, Genetics. 5(4):569-582.
Genomic selection & association mapping in rice: effect of trait genetic architecture, training population composition, marker number & statistical model on accuracy of rice genomic selection in elite, tropical rice breeding Reprint Icon -
Spindel, J., Begum, H., Akdemir, D., Virk, P., Collard, B., Redona, E., Atlin, G., Jannink, J., Mccouch, S.R. 2015. Genomic selection & association mapping in rice: effect of trait genetic architecture, training population composition, marker number & statistical model on accuracy of rice genomic selection in elite, tropical rice breeding. PLoS Genetics. 11(6):e1005350.
Locally epistatic genomic relationship matrices for genomic association Reprint Icon -
Akdemir, D., Jannink, J. 2015. Locally epistatic genomic relationship matrices for genomic association. Genetics. 199:857-871.
solGS: a web-based tool for genomic selection Reprint Icon -
Tecle, I., Edwards, J., Menda, N., Egesi, C., Rabbi, I.Y., Kulakow, P., Kawuki, R., Jannink, J., Mueller, L.A. 2014. solGS: a web-based tool for genomic selection. BMC Bioinformatics. 15:398.
Efficient use of historical data for genomic selection: a case study of rust resistance in wheat -
Rutkoski, J., Singh, R., Huerta-Espino, J., Bhavani, S., Poland, J.A., Jannink, J., Sorrells, M. 2015. Efficient use of historical data for genomic selection: a case study of rust resistance in wheat. The Plant Genome. (8). DOI: 10.3835/plantgenome2014.09.0046.
Training set optimization under population structure in genomic selection Reprint Icon -
Isidro, J., Jannink, J., Akdemir, D., Poland, J., Heslot, N., Sorrells, M. 2015. Training set optimization under population structure in genomic selection. Theoretical and Applied Genetics. 128(1):145-158.
Genomic prediction in bi-parental tropical maize populations in water-stressed and well-watered environments using low density and GBS SNPs Reprint Icon -
Zhang, X., Perez-Rodriquez, P., Kassa, S., Beyene, Y., Babu, R., Lopez Cruz, M., San Vicente, F., Olsen, M., Buckler IV, E.S., Jannink, J., Prasanna, B.M., Crossa, J. 2014. Genomic prediction in bi-parental tropical maize populations in water-stressed and well-watered environments using low density and GBS SNPs. Heredity. 114:291-299.
Assessing genomic selection prediction accuracy in a dynamic barley breeding -
Sallam, A., Endelman, J., Jannink, J., Smith, K. 2014. Assessing genomic selection prediction accuracy in a dynamic barley breeding. The Plant Genome. (8). DOI: 10.3835/plantgenome2014.05.0020.
Perspectives for genomic selection applications and research in plants Reprint Icon -
Heslot, N., Jannink, J., Sorrells, M.E. 2014. Perspectives for genomic selection applications and research in plants. Crop Science. 55:1-12.
Genomic selection for quantitative adult plant stem rust resistance in wheat -
Rutkoski, J.E., Sorrells, M., Poland, J.A., Singh, R.P., Huerta-Espino, J., Bhavani, S., Barbier, H., Rouse, M.N., Jannink, J. 2014. Genomic selection for quantitative adult plant stem rust resistance in wheat. The Plant Genome. DOI: 10.3835/plantgenome2014.02.0006.
Genetic mapping using genotyping-by-sequencing in the clonally-propagated cassava -
Rabbi, I., Hamblin, M., Gedil, M., Kulakow, P., Ferguson, M., Ikpan, A.S., Ly, D., Jannink, J. 2014. Genetic mapping using genotyping-by-sequencing in the clonally-propagated cassava. Crop Science. DOI: 10.2135/cropsci2013.07.0482.
Genomic selection in plant breeding -
Newell, M., Jannink, J. 2013. Genomic selection in plant breeding. In: Fleury, D., and WHitford, R., editors. Crop Breeding: Methods and Protocols. Humana Press, Springer New York, Heidelberg, dordrecht, London. p. 117-130.
High-resolution mapping of resistance to cassava mosaic geminiviruses in cassava using genotyping-by-sequencing and its implications for breeding -
Rabbi, I., Hamblin, M., Kumar, P., Gedil, M., Ikpan, A.S., Jannink, J., Kulakow, P. 2013. High-resolution mapping of resistance to cassava mosaic geminiviruses in cassava using genotyping-by-sequencing and its implications for breeding. Virus Research. 186:87-96.
Integrating environmental covariates and crop modeling into the genomic selection framework to predict genotype by environment interactions -
Heslot, N., Akdemir, D., Sorrells, M.E., Jannink, J. 2013. Integrating environmental covariates and crop modeling into the genomic selection framework to predict genotype by environment interactions. Theoretical and Applied Genetics. 127:463-480.
Micro-enzymatic evaluation of oat (Avena sativa L.) beta-glucan for high-throughput phenotyping -
Newell, M.A., Kim, H., Asoro, F.G., Moran Lauter, A., White, P.J., Scott, M.P., Jannink, J. 2014. Micro-enzymatic evaluation of oat (Avena sativa L.) beta-glucan for high-throughput phenotyping. Cereal Chemistry. 91:183–188.
Genomic prediction in maize breeding populations with genotyping-by-sequencing -
Crossa, J., Beyene, Y., Segman, K., Perez, P., Hickey, J.M., Chen, C., De Los Campos, G., Burgueno, J., Windhausen, V.S., Buckler IV, E.S., Jannink, J., Lopez Crua, M.A., Babu, R. 2013. Genomic prediction in maize breeding populations with genotyping-by-sequencing. Genes, Genomes, Genetics. DOI: 10.1534/g3.113.008227.
Impact of marker ascertainment bias on genomic selection accuracy and estimates of genetic diversity Reprint Icon -
Heslot, N., Rutkoski, J., Poland, J.A., Jannink, J., Sorrells, M.E. 2013. Impact of marker ascertainment bias on genomic selection accuracy and estimates of genetic diversity. PLoS One. 8(9): e74612.
Genotype by environment interaction and the use of unbalanced historical data for genomic selection in an international wheat breeding program -
Dawson, J.C., Endelman, J., Heslot, N., Crossa, J., Poland, J.A., Dreisigacker, S., Manes, Y., Sorrells, M., Jannink, J. 2013. Genotype by environment interaction and the use of unbalanced historical data for genomic selection in an international wheat breeding program. Field Crops Research. 154:12-22.
Optimal design of preliminary yield trials with genome-wide markers -
Endelman, J., Atlin, G., Beyene, Y., Fentaye, K., Zhang, X., Sorrells, M., Jannink, J. 2014. Optimal design of preliminary yield trials with genome-wide markers. Crop Science. 54:48-59.
An algorithm for deciding the number of clusters and validating using simulated data with application to exploring crop population structure -
Newell, M., Cook, D., Hofmann, H., Jannink, J. 2013. An algorithm for deciding the number of clusters and validating using simulated data with application to exploring crop population structure. Annals of Applied Statistics. 7:1898-1916.
Ensemble learning with trees and rules: supervised, semi-supervised, unsupervised Reprint Icon -
Akdemir, D., Jannink, J. 2014. Ensemble learning with trees and rules: supervised, semi-supervised, unsupervised. Intelligent Data Analysis (An International Journal). 18(5):857-872.
Genomic predictability of interconnected bi-parental maize populations Reprint Icon -
Riedelsheimer, C., Endelman, J., Stange, M., Sorrells, M., Jannink, J., Melchinger, A. 2013. Genomic predictability of interconnected bi-parental maize populations. Genetics. 194:493-503.
Comparison of genomic, marker-assisted, and pedigree-BLUP selection methods to increase beta-glucan concentration in elite oat germplasm -
Asoro, F., Newell, M., Beavis, W., Scott, M.P., Tinker, N., Jannink, J. 2013. Comparison of genomic, marker-assisted, and pedigree-BLUP selection methods to increase beta-glucan concentration in elite oat germplasm. Crop Science. 53(5):1894-1906.
SNP discovery and chromosome anchoring provide the first physically-anchored hexaploid oat map and reveal synteny with model species -
Oliver, R.E., Tinker, N.A., Lazo, G.R., Chao, S., Jellen, E.N., Carson, M.L., Rines, H.W., Obert, D., Lutz, J.D., Shackelford, I., Korol, A.B., Wight, C., Gardner, K.M., Hattori, J., Beattie, A., Bjornstad, A., Bonman, J.M., Jannink, J., Mitchell Fetch, J.W., Harrison, S., Howarth, C.J., Ibrahim, A., Kolb, F.L., McMullen, M.S., Murphy, J.P., Ohm, H., Rossnagel, B.G., Yan, W., Miclaus, K.J., Hiller, J., Maughan, P.J., Redman-Hulse, R.R., Anderson, J.M., Islamovic, E., Jackson, E.W. 2013. SNP discovery and chromosome anchoring provide the first physically-anchored hexaploid oat map and reveal synteny with model species. PLoS One. 8:e58068.
The effects of relatedness and GxE interaction on prediction accuracies in genomic selection: a study in cassava -
Ly, D., Hamblin, M., Rabbi, I., Gedli, M., Bakare, M., Gauch, H., Okechukwu, R., Dixon, A., Kulakow, P., Jannink, J. 2013. The effects of relatedness and GxE interaction on prediction accuracies in genomic selection: a study in cassava. Crop Science. 53(4):1312-1325.
Imputation of unordered markers and the impact on genomic selection accuracy Reprint Icon -
Rutkoski, J., Poland, J.A., Jannink, J., Sorrells, M. 2013. Imputation of unordered markers and the impact on genomic selection accuracy. Genetics. 3(3):427-39.
Imputation of unordered markers and the impact on genomic selection accuracy Reprint Icon -
Rutkoski, J., Poland, J.A., Jannink, J., Sorrells, M. 2013. Imputation of unordered markers and the impact on genomic selection accuracy. Genes, Genomes, and Genomics. 3(3):427-439.
Multiple trait genomic selection methods increase genetic value prediction accuracy -
Jia, Y., Jannink, J. 2012. Multiple trait genomic selection methods increase genetic value prediction accuracy. Genetics. 192(4):1513-1522.
Effectiveness of genomic prediction of maize hybrid performance in different breeding populations and environments Reprint Icon -
Weber, V.S., Atlin, G.A., Hickey, J.M., Crossa, J., Jannink, J., Sorrells, M.E., Raman, B., Cairns, J.E., Tarekegne, A., Semagn, K., Beyene, Y., Grudloyma, P., Technow, F., Riedelsheimer, C., Melchinger, A.E. 2012. Effectiveness of genomic prediction of maize hybrid performance in different breeding populations and environments. Genes, Genomes, and Genomics. 2(11):1427-1436.
Shrinkage estimation of the realized relationship matrix Reprint Icon -
Endelman, J.B., Jannink, J. 2012. Shrinkage estimation of the realized relationship matrix. Genes, Genomes, and Genomics. 2(11):1405-1413.
Genomic selection in wheat using genotyping-by-sequencing Reprint Icon -
Poland, J.A., Endelman, J.B., Dawson, J., Rutkoski, J., Wu, S., Manes, Y., Dreisigacker, S., Crossa, J., Sanchez, H., Sorrells, M., Jannink, J. 2012. Genomic selection in wheat using genotyping-by-sequencing. The Plant Genome. 5(3):103-113.
Genomewide association study for beta-glucan content in North American elite oat -
Asoro, F.G., Newell, M.A., Scott, M.P., Beavis, W.D., Jannink, J. 2013. Genomewide association study for beta-glucan content in North American elite oat. Crop Science. 53:542-553.
Genome-wide association study for oat (Avena sativa L.) beta-glucan concentration using germplasm of worldwide origin -
Newell, M., Franco, A., Scott, M.P., White, P., Beavis, W., Jannink, J. 2012. Genome-wide association study for oat (Avena sativa L.) beta-glucan concentration using germplasm of worldwide origin. Theoretical and Applied Genetics. 125:1687-1696.
Using genomic prediction to characterize environments and optimize prediction accuracy in applied breeding data -
Heslot, N., Jannink, J., Sorrells, M. 2013. Using genomic prediction to characterize environments and optimize prediction accuracy in applied breeding data. Crop Science. 53(3):921-933.
The hordeum toolbox - the barley CAP genotype and phenotype resource -
Blake, V.C., Kling, J.G., Hayes, P.M., Jannink, J., Jillella, S.R., Lee, J., Matthews, D.E., Chao, S., Close, T.J., Muehlbauer, G.J., Smith, K.P., Wise, R.P., Dickerson, J.A. 2012. The hordeum toolbox - the barley CAP genotype and phenotype resource. The Plant Genome. DOI: 10.385/plantgenome2012.03.0002.
Evaluation of genomic prediction methods for fusarium head blight resistance in wheat -
Rutkoski, J., Benson, J., Jia, Y., Brown Guedira, G.L., Jannink, J., Sorrells, M. 2012. Evaluation of genomic prediction methods for fusarium head blight resistance in wheat. The Plant Genome. 5:51-61.
Potential and optimization of genomic selection for fusarium head blight resistance in six-row barley -
Lorenz, A.J., Smith, K.P., Jannink, J. 2012. Potential and optimization of genomic selection for fusarium head blight resistance in six-row barley. Crop Science. 52(4):1609-1621. DOI: 10.2135/cropsci2011.09.0503.
Development of high-density genetic maps for barley and wheat using a novel two enzyme genotyping-by-sequencing approach Reprint Icon -
Poland, J.A., Brown, P.J., Sorrells, M.E., Jannink, J. 2012. Development of high-density genetic maps for barley and wheat using a novel two enzyme genotyping-by-sequencing approach. PLoS One. 7(2): e32253.
Accuracy and training population design for genomic selection in elite north american oats -
Asoro, F.G., Newell, M.A., Beavis, W.D., Jannink, J., Scott, M.P. 2011. Accuracy and training population design for genomic selection in elite north american oats. The Plant Genome. 4:132-144.
Factors affecting the power of haplotype markers in association studies -
Hamblin, M., Jannink, J. 2011. Factors affecting the power of haplotype markers in association studies. The Plant Genome. 4:145-153.
Accuracy of genomic selection in barley breeding programs: a simulation study based on the real SNP data -
Population genetics of genomics-based crop improvement methods -
Hamblin, M., Buckler Iv, E.S., Jannink, J. 2011. Population genetics of genomics-based crop improvement methods. Trends in Genetics. 27:98-106.
Genomic selection accuracy using multi-family prediction models in a wheat breeding program -
Heffner, E., Jannink, J., Sorrells, M. 2011. Genomic selection accuracy using multi-family prediction models in a wheat breeding program. The Plant Genome. 4:65-75.
Analysis of genetic diversity using SNP markers in oat -
Chao, S., Oliver, R.E., Lazo, G.R., Tinker, N., Jannink, J., Redman, R.R., Jackson, E.W. 2011. Analysis of genetic diversity using SNP markers in oat. Meeting Abstract. pg. 209.
Population structure and linkage disequilibrium in oat (Avena sativa L.): implications for genome-wide association studies -
Newell, M.A., Cook, D., Tinker, N.A., Jannink, J. 2010. Population structure and linkage disequilibrium in oat (Avena sativa L.): implications for genome-wide association studies. Theoretical and Applied Genetics. 122:623-632.
Performance of single nucleotide polymorphisms versus haplotypes for genome-wide association analysis in barley -
Lorenz, A.J., Hamblin, M.T., Jannink, J. 2010. Performance of single nucleotide polymorphisms versus haplotypes for genome-wide association analysis in barley. PLoS Genetics. 5(II):e14079.
Genomic selection in plant breeding: knowledge and prospects -
Lorenz, A.J., Chao, S., Asoro, F.G., Heffner, E.L., Hayashi, T., Iwata, H., Smith, K.P., Sorrells, M.E., Jannink, J. 2011. Genomic selection in plant breeding: knowledge and prospects. Advances in Agronomy. 110:77-123.
Assessment of power and false discovery in genome-wide association studies using the BarleyCAP germplasm -
Bradbury, P., Parker, T., Hamblin, M.T., Jannink, J. 2010. Assessment of power and false discovery in genome-wide association studies using the BarleyCAP germplasm. Crop Science. 51:52-59.
Dynamics of long-term genomic selection -
Jannink, J. 2010. Dynamics of long-term genomic selection. Genetics. 42:35.
Plant breeding with genomic selection: potential gain per unit time and cost -
Heffner, E.L., Lorenz, A.J., Jannink, J., Sorrells, M.E. 2010. Plant breeding with genomic selection: potential gain per unit time and cost. Crop Science. 50:1681-1690.
Genomic selection in plant breeding: from theory to practice -
Jannink, J., Lorenz, A.J., Iwata, H. 2010. Genomic selection in plant breeding: from theory to practice. Briefings in Functional Genomics and Proteomics. 9:166-177.
Marker genotype imputation in a low-marker-density panel with a high-marker-density reference panel: accuracy evaluation in barley breeding lines -
Iwata, H., Jannink, J. 2010. Marker genotype imputation in a low-marker-density panel with a high-marker-density reference panel: accuracy evaluation in barley breeding lines. Crop Science. 50:1269-1278.
Whole genome association mapping of grain shape variation among Oryza sativa L. germplasms based on elliptic Fourier analysis -
Iwata, H., Ebana, K., Uga, Y., Hayashi, T., Jannink, J. 2009. Whole genome association mapping of grain shape variation among Oryza sativa L. germplasms based on elliptic Fourier analysis. Theoretical and Applied Genetics. 114(8):1437-1449.
Population structure and linkage disequilibrium in US barley germplasm: implications for association mapping -
Hamblin, M.T., Close, T.J., Bhat, P.R., Chao, S., Abraham, K., Blake, T., Brooks, W.S., Cooper, B., Griffey, C.A., Hayes, P.M., Hole, D.J., Horsley, R.D., Obert, D.E., Smith, K.P., Ullrich, S.E., Muehlbauer, G.J., Jannink, J. 2010. Population structure and linkage disequilibrium in US barley germplasm: implications for association mapping. Crop Science. 50:556-566.
Association-Based Genomic Selection in Cultivated Barley -
Zhong, S., Dekkers, J., Jannink, J. 2009. Association-Based Genomic Selection in Cultivated Barley. Genetics. 182:355-364.
Marker imputation in barley association studies -
Jannink, J., Iwata, H., Bhat, P.R., Chao, S., Wenzl, P., Muehlbauer, G.J. 2009. Marker imputation in barley association studies. The Plant Genome. 2:11-22.
New DArT markers for oat provide enhanced map coverage and global germplasm characterization -
Tinker, N.A., Kilian, A., Wright, C.P., Heller-Uszynska, K., Wenzl, P., Rines, H.W., Bjornstad, A., Howarth, C., Jannink, J., Anderson, J.M., Rossnagle, B.G., Stuthman, D.D., Sorrells, M.E., Jackson, E.W., Tuvesson, S., Kolb, F.L., Olsson, O., Federizzi, L.C., Carson, M.L., Ohm, H.W., Molnar, S.J., Scoles, G.J., Eckstein, P.E., Bonman, J.M., Ceplitis, A., Langdon, T. 2009. New DArT markers for oat provide enhanced map coverage and global germplasm characterization. BMC Medical Genetics. 10:39.
Selective Advance for Accelerated Development of Recombinant Inbred QTL Mapping Populations -
Boddhireddy, P., Jannink, J., Nelson, J. 2009. Selective Advance for Accelerated Development of Recombinant Inbred QTL Mapping Populations. Crop Science. 49:1284-1294.
Bayesian multilocus association mapping on ordinal and censored traits and its application to the analysis of genetic variation among Oryza sativa L. germplasms -
Iwata, H., Ebana, K., Fukuoka, S., Hayashi, T., Jannink, J. 2009. Bayesian multilocus association mapping on ordinal and censored traits and its application to the analysis of genetic variation among Oryza sativa L. germplasms. Theoretical and Applied Genetics. 118(5):865-880.
New DArT markers for oat provide enhanced map coverage and global germplasm characterization -
Tinker, N.A., Kilian, A., Rines, H.W., Bjornstad, A., Howarth, C.J., Jannink, J., Anderson, J.M., Rossnagel, B.G., Wight, C.P., Stuthman, D.D., Sorrells, M.E., Scoles, G.J., Eckstein, P.E., Ohm, H.W., Jackson, E.W., Tuvesson, S., Kolb, F.L., Molnar, S.J., Olsson, O., Carson, M.L., Ceplitis, A., Bonman, J.M., Federizzi, L., Langdon, T. 2009. New DArT markers for oat provide enhanced map coverage and global germplasm characterization. Biomed Central (BMC) Genomics. 10(39):1471-2164.
Association genetics in barley -
Waugh, R., Muehlbauer, G.J., Jannink, J., Ramsay, L. 2009. Association genetics in barley. Current Opinion in Plant Biology. 12(2):218-222.
Genomic Selection for Crop Improvement -
Heffner, E.L., Sorrells, M.E., Jannink, J. 2009. Genomic Selection for Crop Improvement. Crop Science. 49:1-12.
Morphological Genetic Diversity of Worldwide Barley and Mega-Targets of Selection -
Gutierrez, L., Nason, J.D., Jannink, J. 2009. Morphological Genetic Diversity of Worldwide Barley and Mega-Targets of Selection. Crop Science. 49:483-497.
Impact of Dry Solids and Bile Acid Concentrations on Bile Acid Binding Capacity of Extruded Oat Cereals -
Yao, N., Jannink, J., White, P.J., Alavi, S. 2008. Impact of Dry Solids and Bile Acid Concentrations on Bile Acid Binding Capacity of Extruded Oat Cereals. Journal of Agricultural and Food Chemistry. 56:8672-8679.
Overview of QTL detection in plants and tests for synergistic epistatic interactions -
Jannink, J., Moreau, L., Charcosset, A., Charmet, G. 2008. Overview of QTL detection in plants and tests for synergistic epistatic interactions. Genetica. 136:225-236.
Size distributions of different orders of kernels within the oat spikelet -
Doehlert, D.C., Jannink, J., Mcmullen, M.S. 2008. Size distributions of different orders of kernels within the oat spikelet. Crop Science. 48:298-340
QTL x Genetic Background Interaction: Application to Predicting Progeny Value -
Jannink, J. 2007. Qtl x genetic background interaction: application to predicting progeny value. Euphytica. 161:61-69.
Using QTL results to discriminate among crosses based on their progeny mean and variance -
Zhong, S., Jannink, J. 2007. Using QTL results to discriminate among crosses based on their progeny mean and variance. Genetics. 177:567-576.
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Last Modified: 5/2/2016
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