Dr. Christina Lehermeier

Research Scientist (Post-doc)

Chair of plant breeding
Technische Universität München

Center of Life and Food Sciences
Liesel-Beckmann-Str. 2
D-85354 Freising

Email: christina.lehermeier[at]tum.de

Phone +49 8161 71-6144
Fax +49 8161 71-4511

Room 3-10

Publications

Lehermeier C, de los Campos G, Wimmer V, Schön C-C (2017) Genomic variance estimates: With or without disequilibrium covariances? Journal of Animal Breeding and Genetics. 134: 232-241 [doi: 10.1111/jbg.12268]

Auinger H-J, Schönleben M, Lehermeier C, Schmidt M, Korzun V, Geiger HH, Piepho H-P, Gordillo A, Wilde P, Bauer E, Schön C-C (2016) Model training across multiple breeding cycles significantly improves genomic prediction accuracy in rye (Secale cereale L.). Theoretical and Applied Genetics. [doi: 10.1007/s00122-016-2756-5]

Livaja M, Unterseer S, Erath W, Lehermeier C, Wieseke R, Plieske J, Polley A, Luerßen H, Wieckhorst S, Mascher M, Hahn V, Ouzunova M, Schön CC, Ganal MW (2016) Diversity analysis and genomic prediction of Sclerotinia resistance in sunflower using a new 25 K SNP genotyping array. Theoretical and Applied Genetics. 129: 317-329 [doi: 10.1007/s00122-015-2629-3]

de los Campos G, Veturi Y, Vazquez AI, Lehermeier C, Pérez-Rodríguez P (2015) Incorporating genetic heterogeneity in whole-genome regressions using interactions. Journal of Agricultural, Biological, and Environmental Statistics. 20: 467-490 [doi: 10.1007/s13253-015-0222-5] (best paper in JABES 2015)

Lehermeier C (2015) Investigation of genome-based prediction in differentially structured plant populations. Dissertation, Technische Universität München, Freising

Lehermeier C, Schön CC, de los Campos G (2015) Assessment of genetic heterogeneity in structured plant populations using multivariate whole-genome regression models. Genetics. 201: 323-337 [doi: 10.1534/genetics.115.177394]

Giraud H, Lehermeier C, Bauer E, Falque M, Segura V, Bauland C, Camisan C, Campo L, Meyer N, Ranc N, Schipprack W, Flament P, Melchinger AE, Menz M, Moreno-Gonzalez J, Ouzunova M, Charcosset A, Schön CC, Moreau L (2014) Linkage disequilibrium with linkage analysis of multi-line crosses reveals different multi-allelic QTL for hybrid performance in the flint and dent heterotic groups of maize. Genetics. 198: 1717-1734 [doi:10.1534/genetics.114.169367]

Lehermeier C, Krämer N, Bauer E, Bauland C, Camisan C, Campo L, Flament P, Melchinger AE, Menz M, Meyer N, Moreau L, Moreno-González J, Ouzunova M, Pausch H, Ranc N, Schipprack W, Schönleben M, Walter H, Charcosset A, Schön CC (2014) Usefulness of multiparental populations of maize (Zea mays L.) for genome-based prediction. Genetics. 198: 3-16 [doi: 10.1534/genetics.114.161943]

Schön C-C, Wimmer V, Lehermeier C (2014) Efficiency of variable selection in genome-wide prediction for traits of different genetic architecture. Proceedings, 10th World Congress of Genetics Applied to Livestock Production

Lehermeier C, Wimmer V, Albrecht T, Auinger HJ, Gianola D, Schmid VJ, Schön CC (2013) Sensitivity to prior specification in Bayesian genome-based prediction models. Statistical Applications in Genetics and Molecular Biology. 12: 375–391 [doi: 10.1515/sagmb-2012-0042]

Wimmer V, Lehermeier C, Albrecht T, Auinger H-J, Wang Y, Schön C-C (2013) Genome-wide prediction of traits with different genetic architecture through efficient variable selection. Genetics. 195: 573-587 [doi: 10.1534/genetics.113.150078]

Talks

Assessment of genetic heterogeneity using whole-genome regression models. 1st French-German Maize Breeders School, Hohenheim, May 24 2017

Genomic variance estimates and their usefulness in breeding. International Conference on "Selection Theory and Breeding Methodology", Freising, March 23 2017

Genome-based prediction across multiple breeding cycles. Illinois Corn Breeders' School, March 6-7 2017

GWAS and genomic prediction across multiple breeding cycles. International conference on Statistics and Big Data in Informatics in Agricultural Research, ICRISAT, Hyderabad, November 22 2016

Assessment of genetic heterogeneity in structured plant breeding populations using multivariate whole-genome regression models. XVIth EUCARPIA Biometrics in Plant Breeding Conference, Wageningen, September 9 2015

Usefulness of multiparental populations of maize for genome-based prediction. GPZ Tagung, Kiel, September 25 2014

Posters

Genomic variance estimates: with or without disequilibrium covariances? Gordon Research Conference: Quantitative Genetics & Genomic, Galveston, TX, USA February 26 - March 3 2017

Genome-based prediction of testcross performance with different testers in hybrid rye breeding. International Conference on Quantitative Genetics, Madison, WI, USA June 12-17 2016

Genome-based prediction of testcross performance with different testers in hybrid rye breeding. GPZ Tagung, Bonn, March 8-10 2016 (1st place poster award)

Assessment of genetic heterogeneity in a maize breeding population using multivariate whole-genome regression models. Synbreed Colloquium, Freising, March 04-06 2015

Assessment of genetic heterogeneity in structured plant breeding populations using multivariate whole-genome regression models. Gordon Research Conference: Quantitative Genetics & Genomics, Lucca, February 22-27 2015

Genomic prediction of testcross performance in multi-line crosses of maize (Zea mays L.). XVth EUCARPIA Biometrics in Plant Breeding Conference, Hohenheim, September 05-07 2012 

Sensitivity to Prior Specification in Bayesian Models for Genomic Prediction in Maize. 4th International Conference on Quantitative Genetics, Edinburgh, June 17-22 2012