Preprints

Bird, K.A., Turner, S.D., Beissinger, T.M., Angelovici, R. Subset-based genomic prediction provides insights into the genetic architecture of free amino acid levels in dry Arabidopsis thaliana seeds. bioRxiv. DOI: 10.1101/272047

2018

Beissinger, T.M., Kruppa, J., Cavero, D., Ha, N., Erbe, M., Simianer, H. A simple test identifies selection on complex traits. Genetics. DOI: 10.1534/genetics.118.300857

2017

Wang, L., Beissinger, T.M., Lorant, A., Ross-Ibarra, C., Ross-Ibarra, J., Hufford, M. The interplay of demography and selection during maize domestication and expansion. Genome Biology. DOI: 10.1186/s13059-017-1346-4.

Beissinger, T.M., Morota, G. 2017. Medical subject heading (MeSH) annotations illuminate maize genetics and evolution Plant Methods. DOI: 10.1186/s13007-017-0159-5.

2016

Morota, G, Beissinger, T.M., Penagaricano, F. MeSH annotation of the chicken genome: MeSH-informed enrichment analysis and MeSH-guided semantic similarity among functional terms and gene products Genes Genomes Genetics. DOI: 10.1534/g3.116.031096.

Beissinger, T.M., Wang, L., Crosby, K., Durvasula, A., Hufford, M.B., Ross-Ibarra, J. 2016. Recent demography drives changes in linked selection across the maize genome. Nature Plants. DOI: 10.1038/NPLANTS.2016.84.

2015

Beissinger, T.M., Gholami, M., Erbe, M., Weigend, S., Weigend, A., de Leon, N., Gianola, D., Simianer, H. 2015. Using the variability of linkage disequilibrium between subpopulations to infer sweeps and epistatic selection in a diverse panel of chickens. Heredity. DOI: 10.1038/hdy.2015.81.

Haase, N.J., Beissinger, T.M., Hirsch, C.N., Vaillancourt, B., Deshpande, S., Barry, K., Buell, C.R., Kaeppler, S., de Leon, N. 2015. Genetic Dissection of quantita- tive traits using a bulked segregant analysis (BSA)-sequencing method on a large segregating population of maize. Genes Genomes Genetics. DOI: 10.1534/g3.115.017665.

Beissinger, T.M., Rosa, J.G.M., Kaeppler, S.M., de Leon, N., Gianola, D. 2015. Defining window-boundaries for genomic analyses using smoothing spline techniques. Genetics Selection Evolution. 47(30). DOI: 10.1186/s12711-015-0105-9.

Lorenz, A. J., Beissinger, T.M., Rodrigues, R., de Leon, N. 2015. Selection for silage yield and composition did not affect genomic diversity within the Wisconsin QualitySynthetic maize population. Genes Genomes Genetics. DOI: 10.1534/g3.114.015263.

Foerster, J.M., Beissinger, T.M., de Leon, N., Kaeppler, S.M. 2015. Large effectQTL explain natural phenotypic variation for the developmental timing of vegetative phase change in maize (Zea mays L.). Theoretical and Applied Genetics. DOI: 10.1007/s00122-014-2451-3.

2014

Hirsch, C.N., Flint-Garcia, S.A., Beissinger, T.M., Eichten, S.R., Deshpande, S., Barry, K., McMullen, M.D., Holland, J.B., Buckler, E.S., Springer, N.M., Buell, C.R., de Leon, N., Kappler, S.M. 2014. Insights into the effects of long-term artificial selection on seed size in maize. Genetics. 198(1): 409-421.

Beissinger, T.M., Hirsch, C.N., Vaillancourt, B., Deshpande, S., Barry, K., Buell, C. R., Kaeppler, S. M., Gianola, D., de Leon, N. 2014. A genome-wide scan for evidence of selection in a maize population under long-term artificial selection for ear number. Genetics. 196(3): 829-840.

2013 and earlier

*Beissinger, T.M., Hirsch, C.N., Sekhon, R.S., Foerster, J.M., Johnson, J.M., Muttoni, G., Vaillancourt, B., Buell, C.R., Kaeppler, S.M., de Leon, N. 2013. Marker density and read-depth for genotyping populations using genotyping-by-sequencing. Genetics. 193: 1073-1081.
* Selected as a highlighted article by the editorial board.

Wu, X., Chuanyu, S., Beissinger, T.M., Rosa, G., Weigel, K., de Leon, N., Gianola, D. 2012. Parallel Markov chain Monte Carlo - bridging the gap to high performance Bayesian computation in animal breeding and genetics. Genet Sel Evol. 44:29.

Wu, X., Beissinger, T.M., Bauck, S., Woodward, B., Rosa, G., Weigel, K., de Leon, N., Gianola, D. 2011. A primer on high-throughput computing for genomic selection. Frontiers in Genetics. 2, 4.