@article{peiffer_romay_gore_flint-garcia_zhang_millard_gardner_mcmullen_holland_bradbury_et al._2014, title={Causes and Consequences of Genetic Background Effects Illuminated by Integrative Genomic Analysis}, volume={196}, ISSN={["1943-2631"]}, DOI={10.1534/genetics.113.159426}, abstractNote={Abstract
               The phenotypic consequences of individual mutations are modulated by the wild-type genetic background in which they occur. Although such background dependence is widely observed, we do not know whether general patterns across species and traits exist or about the mechanisms underlying it. We also lack knowledge on how mutations interact with genetic background to influence gene expression and how this in turn mediates mutant phenotypes. Furthermore, how genetic background influences patterns of epistasis remains unclear. To investigate the genetic basis and genomic consequences of genetic background dependence of the scallopedE3 allele on the Drosophila melanogaster wing, we generated multiple novel genome-level datasets from a mapping-by-introgression experiment and a tagged RNA gene expression dataset. In addition we used whole genome resequencing of the parental lines—two commonly used laboratory strains—to predict polymorphic transcription factor binding sites for SD. We integrated these data with previously published genomic datasets from expression microarrays and a modifier mutation screen. By searching for genes showing a congruent signal across multiple datasets, we were able to identify a robust set of candidate loci contributing to the background-dependent effects of mutations in sd. We also show that the majority of background-dependent modifiers previously reported are caused by higher-order epistasis, not quantitative noncomplementation. These findings provide a useful foundation for more detailed investigations of genetic background dependence in this system, and this approach is likely to prove useful in exploring the genetic basis of other traits as well.}, number={4}, journal={GENETICS}, author={Peiffer, J. A. and Romay, M. C. and Gore, M. A. and Flint-Garcia, S. A. and Zhang, Z. W. and Millard, M. J. and Gardner, C. A. C. and McMullen, M. D. and Holland, James and Bradbury, P. J. and et al.}, year={2014}, month={Apr}, pages={1321-+} }
 @article{huang_massouras_inoue_peiffer_ramia_tarone_turlapati_zichner_zhu_lyman_et al._2014, title={Natural variation in genome architecture among 205 Drosophila melanogaster Genetic Reference Panel lines}, volume={24}, number={7}, journal={Genome Research}, author={Huang, W. and Massouras, A. and Inoue, Y. and Peiffer, J. and Ramia, M. and Tarone, A. M. and Turlapati, L. and Zichner, T. and Zhu, D. H. and Lyman, R. F. and et al.}, year={2014}, pages={1193–1208} }
 @article{peiffer_romay_gore_flint-garcia_zhang_millard_gardner_mcmullen_holland_bradbury_et al._2014, title={The Genetic Architecture Of Maize Height}, volume={196}, ISSN={["1943-2631"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84901312138&partnerID=MN8TOARS}, DOI={10.1534/genetics.113.159152}, abstractNote={Abstract
               Height is one of the most heritable and easily measured traits in maize (Zea mays L.). Given a pedigree or estimates of the genomic identity-by-state among related plants, height is also accurately predictable. But, mapping alleles explaining natural variation in maize height remains a formidable challenge. To address this challenge, we measured the plant height, ear height, flowering time, and node counts of plants grown in >64,500 plots across 13 environments. These plots contained >7300 inbreds representing most publically available maize inbreds in the United States and families of the maize Nested Association Mapping (NAM) panel. Joint-linkage mapping of quantitative trait loci (QTL), fine mapping in near isogenic lines (NILs), genome-wide association studies (GWAS), and genomic best linear unbiased prediction (GBLUP) were performed. The heritability of maize height was estimated to be >90%. Mapping NAM family-nested QTL revealed the largest explained 2.1 ± 0.9% of height variation. The effects of two tropical alleles at this QTL were independently validated by fine mapping in NIL families. Several significant associations found by GWAS colocalized with established height loci, including brassinosteroid-deficient dwarf1, dwarf plant1, and semi-dwarf2. GBLUP explained >80% of height variation in the panels and outperformed bootstrap aggregation of family-nested QTL models in evaluations of prediction accuracy. These results revealed maize height was under strong genetic control and had a highly polygenic genetic architecture. They also showed that multiple models of genetic architecture differing in polygenicity and effect sizes can plausibly explain a population’s variation in maize height, but they may vary in predictive efficacy.}, number={4}, journal={GENETICS}, author={Peiffer, Jason A. and Romay, Maria C. and Gore, Michael A. and Flint-Garcia, Sherry A. and Zhang, Zhiwu and Millard, Mark J. and Gardner, Candice A. C. and McMullen, Michael D. and Holland, James B. and Bradbury, Peter J. and et al.}, year={2014}, month={Apr}, pages={1337-+} }
 @article{romay_millard_glaubitz_peiffer_swarts_casstevens_elshire_acharya_mitchell_flint-garcia_et al._2013, title={Comprehensive genotyping of the USA national maize inbred seed bank}, volume={14}, ISSN={["1474-760X"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84878685948&partnerID=MN8TOARS}, DOI={10.1186/gb-2013-14-6-r55}, abstractNote={Genotyping by sequencing, a new low-cost, high-throughput sequencing technology was used to genotype 2,815 maize inbred accessions, preserved mostly at the National Plant Germplasm System in the USA. The collection includes inbred lines from breeding programs all over the world.The method produced 681,257 single-nucleotide polymorphism (SNP) markers distributed across the entire genome, with the ability to detect rare alleles at high confidence levels. More than half of the SNPs in the collection are rare. Although most rare alleles have been incorporated into public temperate breeding programs, only a modest amount of the available diversity is present in the commercial germplasm. Analysis of genetic distances shows population stratification, including a small number of large clusters centered on key lines. Nevertheless, an average fixation index of 0.06 indicates moderate differentiation between the three major maize subpopulations. Linkage disequilibrium (LD) decays very rapidly, but the extent of LD is highly dependent on the particular group of germplasm and region of the genome. The utility of these data for performing genome-wide association studies was tested with two simply inherited traits and one complex trait. We identified trait associations at SNPs very close to known candidate genes for kernel color, sweet corn, and flowering time; however, results suggest that more SNPs are needed to better explore the genetic architecture of complex traits.The genotypic information described here allows this publicly available panel to be exploited by researchers facing the challenges of sustainable agriculture through better knowledge of the nature of genetic diversity.}, number={6}, journal={GENOME BIOLOGY}, author={Romay, Maria C. and Millard, Mark J. and Glaubitz, Jeffrey C. and Peiffer, Jason A. and Swarts, Kelly L. and Casstevens, Terry M. and Elshire, Robert J. and Acharya, Charlotte B. and Mitchell, Sharon E. and Flint-Garcia, Sherry A. and et al.}, year={2013} }
 @article{peiffer_flint-garcia_de leon_mcmullen_kaeppler_buckler_2013, title={The genetic architecture of maize stalk strength}, volume={8}, number={6}, journal={PLoS One}, author={Peiffer, J. A. and Flint-Garcia, S. A. and De Leon, N. and McMullen, M. D. and Kaeppler, S. M. and Buckler, E. S.}, year={2013} }
 @article{huang_carbone_magwire_peiffer_lyman_stone_anholt_mackay, title={Genetic basis of transcriptome diversity in Drosophila melanogaster}, volume={112}, number={44}, journal={Proceedings of the National Academy of Sciences of the United States of America}, author={Huang, W. and Carbone, M. A. and Magwire, M. M. and Peiffer, J. A. and Lyman, R. F. and Stone, E. A. and Anholt, R. R. H. and Mackay, T. F. C.}, pages={E6010–6019} }